![2 Vision on CONASENSE Architecture
identity/location and the time. In addition, sufficiently large bandwidths are
allocated to navigation services so as to allow accurate position determination
and transmission/reception of navigation signals. Similar arguments may be
repeated for communication and sensor systems. In view of this and the fact
that modern telecommunication systems support very high data rates, strongly
needed integration of digital COmmunications, NAvigation, SENsing and
related Services (CONASENSE) looks feasible (see Figure 1.1). The technol-
ogy is believed to be available for the integration of CONASENSE-related ser-
vices under realistic scenarios. The emphasis of the CONASENSE Initiative
[1], [2] is on the improvement of the quality of life (QoL) of human beings in
harmony with the environment using the available and enabling technologies.
The CONASENSE mission also includes helping the development of innova-
tive technologies for mid- to far-terms. The QoL is believed to be improved
when human beings can choose freely between sufficiently many user-friendly
CONASENSE services which do not compromise the user-privacy.
Covering a large domain of research, the CONASENSE has a high
potential for a variety of applications and service provision to a large spectrum
of users. Consequently, the CONASENSE-related studies may be research-
oriented, e.g., related to system architecture, performance evaluation, protocol
design, physical layer techniques etc.; application-oriented, e.g., proof-of-
concept studies, system or prototype development; and/or service-oriented,
including approaches for the provision of a multitude of services. These
services may be related to, for example, health, monitoring and protection
of the environment, traffic-control and security.
Figure 1.1 The CONASENSE framework
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![1.2 Requirements 3
Section 2 will present the requirements for present and future
CONASENSE services. Section 3 will provide architectural considerations
related to the CONASENSE-related technologies and services with emphasis
on areas including e-Health, security, traffic control, environment monitoring
and protection. The CONASENSE architecture aims to specify how the
infrastructures related to communications, sensing and navigation should
interact so as to provide the desired QoLservices.Architectural considerations
will be presented for the evolution of CONASENSE services with time even
though long-term predictions may not be easy. The problems and drawbacks
of the current infrastructures and architectures will be reviewed, and backward
compatibility issues will be briefly discussed.
1.2 Requirements
QoL improvement by developing novel CONASENSE systems requires
strategy for and design of integrated architecture that meets the technical
requirements at system level and for all interfaces (terminals, equipment,
person to machine, M2M [3–5]) as well as technical requirements for receiver
and system design. Hence, integrated synergistic use of CONASENSE-
capabilities is mandatory. Flexible, intelligent, and heterogeneous architecture
of the system must operate with any kind of enabled devices (i.e., fixed,
portable and handheld ones) and control centers, and the services must
be provided by, amongst others, satellite and terrestrial segments. The use
of advanced cognitive, cooperative and context− and location-aware tech-
nologies and distributed system intelligence and application programmable
interfaces (API) are strongly desired. The architecture should be intelligent
with sensing, learning, decision and action functions, with the exploitation of
the benefits of clouds of users; reconfigurable, adaptive, energy efficient; high
efficiency, capacity satisfying QoS requirements; support security demands;
incorporate context awareness; integrate available technologies and provide
the optimization of the architecture for various applications. The middleware
should integrate all heterogeneous components (localization, communication
and sensing) in a common stratum to implement the basic functionalities for
all the services. On top of the middleware the applications should provide the
complex system intelligence functionalities.
QoL improvement can be fastened via multi-disciplinary academic and
applied research, which requires international institutional cooperation and
the presence of test laboratories with state-of-the-art test and measure-
ment equipment. Main criterion for developing novel CONASENSE system
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![1.2 Requirements 5
might be of vital importance in certain scenarios. The privacy and surviv-
ability may be required for many services. The cognition, self-organization
capability and adaptability of the terminals against different environmental
and operational conditions are strongly desired. In addition to all these, these
services must be ubiquitous, reliable and affordable.
1.2.3 Technical Requirements for Receiver and System Design
The frequency bands allocated to CONASENSE services differ depending
on the particular application. Consequently, the propagation channels behave
differently and the requirements for transceiver design are not the same.
Depending on the applications and the related services, the operating fre-
quency bands may cover radio frequency (RF), optical, infrared (IR), acoustics
etc. A common (integrated) and interoperable receiver for CONASENSE
services is required to operate at different frequency bands, transmit power
levels, receiver sensitivities, antenna structures, single- and multi-carrier
transmissions techniques and modulation schemes [6–9]. Improved position-
ing accuracy by integration of the navigation data collected from different
sources, such as global positioning system (GPS), Galileo, GLONASS, Wi-Fi,
gyroscopes, accelerometers etc., is strongly desired.
Software-defined radio (SDR) may be considered as a strong candidate
for an integrated receiver. Present technologies allow the design of agile
front-ends with frequency synthesizers of fast hopping and settling times and
with low phase noise. Followed by fast analog-to-digital and digital-to-analog
convertors, the present signal processing technology facilitates the design of
common low-noise and sensitive SDR receivers, by using a DSP chip, ASIC
or FPGA, operating at numerous frequency bands and interoperable with dif-
ferent systems [10], [11]. A multi-band SDR for spaceborne communications,
navigation, radio science and sensors is reported to support communication,
command and telemetry links, high-rate scientific data return links and two-
way Doppler navigation. Modularity within core hardware and firmware
platforms allow for additional software and software upgradeable features,
technology enhancements and implementations with minimal non-recurring
engineering costs [12], [13].
In view of the above, system architecture design which would enable
integrated CONASENSE services is a challenging task. One of the
first issues to be resolved in this context concerns the interoperabil-
ity with LTE/4G, professional mobile radio (PMR) and/or terrestrial and
satellite-based navigation systems [13]. In view of the anticipated diverse
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![6 Vision on CONASENSE Architecture
applications, direct communications and multi-hop relaying between different
user equipment without using base stations may also be required. Other
issues to be concerned include broadcasting, multicasting, security, routing,
radio resource management, efficient power/energy consumption, network
establishment etc.
1.2.4 Energy Requirements
Energy is a valuable resource in CONASENSE-related applications. Design
of battery- or electricity-operated wireless communications and sensor nodes
are based on continuous flow of power from the energy/power source to
the electronic equipment. If electricity or battery is not available on-site,
the systems may be operated by harvesting energy from their environment.
Energy harvesting implies the collection of energy from ambient sources
and converting into electrical energy. However, irrespective of whether the
required electric energy is provided by the mains, the battery or energy
harvesting, minimization of the consumed energy is strongly desired because
of reasons such as cost, equipment life-time, electromagnetic compatibility
and for future innovative applications [14].
From an energy perspective, a communication or a sensor node may be
considered to be composed of supply and demand sides. A sensor node differs
from a communication node mainly by the presence of a sensor. The demand
side consists of energy consuming units such as a sensor, a signal processing
unit, a wireless transceiver and a buffer, either to store the sensed data or the
data to be transmitted/received [15], [16].Transceivers typically use Bluetooth
or Zigbee protocols to communicate within a range of maximum 30 m and
require output power levels in the order of 2–100 mW. Hence, power levels
needed by a sensor node may be in the order of few 100 mWs including all
components. The supply side of a node consists of energy storage and energy
harvester in energy harvesting systems. Using the harvested energy and/or
the battery, it communicates via its transceiver with outside world; it receives
orders from and transmits the sensed data to its base station. The lifetime of
energy harvesting systems is theoretically infinite.
Wirelesssensornodesareusuallybattery-operatedbecauseofthedifficulty
and/or inconvenience of reaching sensor nodes in remote locations, high cost
of maintenance and replacement. Hence, the energy efficiency determines
the life-time of battery-operated sensor nodes, which are required to provide
independent, sustainable and continuous operation. Battery-operated nodes do
not have an energy harvester and the node life-time is limited by the battery
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![1.2 Requirements 7
capacity. Recently remarkable improvements are observed in power density
(W/kg), efficiency, amount of supplied power and the capacity (Amp.-hour)
in the area of energy storage [17]. Nevertheless, operation by batteries still
has its limitations and may not be suitable for certain applications.
Hence, there is strong demand for energy harvesting systems that can
generate their own energy from their environment. Since energy harvesting
may not always be available and predictable, energy harvesting systems
employ batteries for storing the harvested energy for present/future use. In
this respect, the harvesting efficiency and the availability of energy source
are the fundamental issues to be considered. Since the present designs are
presently based on the continuous flow and ever-presence of the electric
energy, these nodes may not operate optimally with energy harvesting and a
novel approaches are required for designs with energy harvesting. Therefore,
energy harvesting nodes should be designed so as to account for the limitations
due to scarcity, non-uniform flow and limited-availability of power in some
time intervals which cannot be predicted beforehand. The CONASENSE
architecture should allow for energy harvesting in mid- to far-terms.
1.2.4.1 Intelligent Designs for Self-Powered
(Energy Harvesting) Nodes
Classical design of sensor/communication nodes is based on the availability
of a continuous flow of a constant power level (infinite energy) to the
demand side. On one hand, dramatic reductions are strongly desired in
power/energy levels dissipated on the demand side of existing wireless
nodes. The energy consumption in transceivers may be decreased by reducing
the data to be transmitted using source coding, choosing adaptive channel
coding and modulation strategies, using efficient transmission scheduling,
exploiting power saving modes (sleep/listen) and using energy efficient
routing and medium access control [18], [19]. On the other hand, energy
harvesting technology is presently far from satisfying present needs. Energy
sources may be (un)controllable and/or (un)predictable for energy harvesting;
solar energy is predictable but uncontrollable, while RF energy harvesting
in a RFID system may be controllable and predictable at the same time.
Therefore, limited power/energy that can be harvested sets a constraint
on the average power or energy consumed by the demand side for self-
powered operation.This implies that energy harvesting, storing and processing
technologies should be improved so as to help sustainable and continuous
operation.
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![8 Vision on CONASENSE Architecture
Even if infinite energy becomes available to the supply side, energy
generation may not be continuous and/or rate of generation may be lim-
ited. Storing the harvested energy may partially alleviate this problem
since it may regulate the power flow. Nevertheless, electronic devices with
classical design cannot reliably operate under these conditions. Therefore,
energy generation profile of the supply side should be matched to the
energy consumption profile of the demand side. This requires a system-
level approach involving variation-tolerant architectures, ultra-low voltage
and highly digital RF circuits. In addition, one needs DSP architecture
and circuits which are energy-efficient, energy-scalable, and robust to vari-
ations in the output of the supply side. Energy-scalable hardware may
call for techniques for approximate processing, which implies a trade-off
between power and arithmetic precision [20]. In wireless sensor networks,
the demand side may be designed with sleep/awake periods in synchronism
with energy harvesting by the supply side. Energy consumption policy may
be optimized in seeking a tradeoff between the throughput and the life-
time of the sensor node [21]. Such approaches are believed to result in
more than an order of magnitude energy reduction compared to present
systems [22].
In some projects like Pico Radio (Berkeley), μAMPS (MIT), WSSN (ICT
Vienna) and GAP4S (UTDallas), densely populated low-cost sensor nodes are
foreseen to operate with power levels of approximately 100 μW; such power
levels is believed to be within the capabilities of energy harvesting. Even
though dramatic improvements are still needed, rapidly-evolving energy har-
vesting technologies are believed to be promising for self-powered operation.
The CONASENSE architecture in the mid- to long-term should address the
energy harvesting problem especially in the mobile communication platforms
and wireless sensors.
The use of nanogenerators is foreseen to be used for a variety of
applications including intra-body drug delivery, health monitoring, medical
imaging, environmental research (air pollution control), military applications
(surveillance networks against nuclear, biological, and chemical attacks at
nanoscale, and home security), and very high data rate communications.
Energy harvesting may enable the widespread use of the nanotechnology [23].
In addition to energy harvesting, the energy problem may be alleviated
by using cognitive approaches and distributed and cooperative data process-
ing among communication and sensor nodes. Beamforning in WSN also
needs to be considered for CONASENSE architectures with reduced energy
consumption.
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![1.3 Architecture 11
testing of different sub-systems while some others assume the responsi-
bility for performance testing of the integrated system and user interface
performance.
Novel architecture design approaches should be jointly considered with
backward compatibility issues since new systems need to be integrated with
the existing ones. Similarly, horizontal integration is also needed between
networks for communications, navigation and sensors. Potential architecture
solutions should also be based on trade-offs between the cost and innovative
content.
Efforts for modeling the architectures facilitate the comparison of both
existing and proposed architectures in order to determine sources of technical
challenges in implementation and facilitate the estimation of the implementa-
tion and operational costs. Risk assessment evaluations are also necessary.
Developing a figure-of-merit help enabling the quantitative evaluation of
each architecture and operational process option. Modular system designs,
approches for system operation as well as software and hardware fixes and
maintenance should be should be carefully considered [24].
1.3.1 Positioning
Positioning, location finding and navigation plays a crucial role in
CONASENSE applications. Accurate, reliable and real-time positioning is a
serious issue in the operation of location-aware services, e.g., in the formation
and self-organization of ad hoc networks [25], in navigation and sensing [26],
emergency conditions etc.
Existing positioning systems have different waveforms, operational fre-
quencies and capabilities. In addition, different frequency bands are allo-
cated to navigation, communications and sensing systems. Therefore, the
CONASENSE architecture should optimize data collection and decision
making in central or distributed ways for improved positioning accuracy. The
recent advances in positioning techniques is believed to improve the position-
ing accuracy in indoor and outdoor environments and pave the way for many
innovative CONASENSE applications even in the near future. Recent tech-
nological developments e.g. in micromechanical systems (MEMS), enables
the development of gyroscopes and accelerometers at smaller sizes to be
incorporated in mobile terminals. Similarly, the use of multiple-input multiple-
output (MIMO) techniques is expected to improve not only the performance
of the communication systems but also help for accurate position and time
estimation. Intense research efforts are going on for the integrated design of
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![12 Vision on CONASENSE Architecture
navigation systems for improved time and position estimation. Telecommu-
nications, sensing and navigation communities are interested in bio-inspired
algorithms [27] for improving the performance of CONASENSE-related ser-
vices. Evolution-perfected bio-algorithms for colony life, migration of fishes,
bees [28], ants, birds and herds inspire the scientists to exploit bio-inspired
algorithms more aggressively.
Positioning systems are usually categorized as network-based or mobile-
based depending on the location where position calculations are per-
formed. Calculations for position estimation may be mobile-based, when the
positioning information is extracted from the received signals, or network-
based if information collected through reference terminals is processed at a
central unit. Positioning systems may be either terrestrial-based and used for
both outdoor and indoor environments, or satellite-based, which offer global
coverage but generally serve to only outdoor users.
Satellites can play a leading role in CONASENSE services due to their
immunity against ground-based catastrophic events and for their ability of col-
lecting information created by sensors deployed on the surface of the earth and
the sky, if necessary. They can provide communications, sensing and enable
assisted localization, combining information from positioning satellites and
terrestrial terminals. Efficient architecture design of hybrid terrestrial-satellite
positioning systems and their integration with communication systems is a
challenging problem. Multiband receiver antennas are needed for operation
in the frequency bands allocated to navigation, sensing and communication
systems. Transmit antennas should be designed so as to produce signals
with isotropic power spectral density within global coverage for navigation
receivers [29].
Indoor positioning, integration of positioning with payment systems,
positioning in live tissues, e.g., in human body, underwater positioning,
positioning in tunnels, positioning of chemical pollutants in the air are among
the numerous areas to be discovered.
1.3.2 Sensing
Recent advances in digital technology enabled the development and pro-
duction of high resolution, low-power, environment-friendly, long-life, low-
cost and small-size sensors [30], [31]. Consequently, we observe in our
everyday life various sensor types, including RFID-, MEMS-, biometric-,
acoustic-, video-sensors and so on. Sensors are used in a very large spectrum
of applications, including health monitoring [32], [33], underwater acoustic
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![1.3 Architecture 13
networks [34], smart grid applications [35], agriculture [36], emergency
applications, automotive industry [37] etc. Therefore, applications related to
sensingwilldefinitelyhaveanincreasingimportanceinCONASENSE-related
applications.
Sensors may be used for sensing locally or remotely; the information
collected by the sensed signals may be processed in situ, in a distributed
fashion, or at a fusion center [38], [39]. Multiple sensors may be employed for
cooperative sensing when the data collected by a single sensor does not meet
the requirements. Data collection, processing and management architecture
and techniques, e.g., sensor fusion, data fusion and/or information fusion, and
making an optimum multi-criteria decision concerning the sensed data, need
to be carefully considered in the design of the CONASENSE architecture.
Heterogeneous networks of sensors may be remotely located from each
other and operate at different frequency bands. For example, in a mar-
itime environment, there are various technologies for detection and locating
objects such as coastal radar, sonar, video camera, IR, automatic identifi-
cation system, automatic vessel locating. In addition, these signals should
be processed with HF communications, intelligence data etc. Moreover,
centralized or decentralized fusion of the information provided by vari-
ous sensors may be required to ensure reliable performance for handling
complex scenarios due to temporary loss of availability, error, limits of
coverage etc. A multi-sensor tracking and information fusion methodol-
ogy /architecture is needed to harness the effectiveness of multiple sensor
information [40].
Recent research efforts on electronic nose, electronic eye and electronic
tongue lead to versatile and innovative applications. Sensing and monitoring
volatile organic compounds, atmospheric pollution, hazardous gases, chem-
icals and explosives may be cited among the applications for security and
environmental protection. In health-related applications, one may cite the
diagnosis of lung cancer at early stage, identification of urinary tract infection
and helicobacter as well as detection, discrimination and monitoring of drug,
drug users and smokers. Sensor systems are also used for building artificial
nose, tongue and eye for robots and other applications as cited in the literature
[41], [42].
A remarkable area that has to be emphasized in the future CONASENSE
applications is the amount of data exchanged in the wireless sensor networks
(WSN). The data across all levels of the network may be generated by smart
sensing systems, supervisory control and data acquisition systems, wide area
monitoring systems, and other sensing/monitoring devices. The huge amounts
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![14 Vision on CONASENSE Architecture
of data and information need to circulate and be stored among control centers,
devices and users. Therefore, the use of data compression techniques will
be desirable to help mitigating the burden of the communication among
CONASENSE sensors and control systems. To this end, the information
acquired by the sensors should be compressed at the sending terminals
as much as possible, before sending through the wireless communication
system. The compression should preserve the valuable information con-
tained in the data, and the compressed data- when received at receiving
terminals- should be perfectly reconstructed too for analysis. In this regard,
the Wavelet technology for data compression is of paramount importance [43]
for the future CONASENSE applications. With this technology data can be
compressed before it is sent out in order to mitigate the data congestion in the
intelligent sensing network. Due to the nature of wavelets, the technique is
beneficial not only in reducing white noise but also in the mitigation of a wide
range of interferences which are present in different application scenarios of
CONASENSE.
Another important issue in sensing area, in general, and in the wireless
sensor networks, in particular, is the self-configuration and self-organization
feature of these networks, or, in other words, the cognitive aspect of
smart WSN. Intelligent CONASENSE sensors are aimed to transform the
already existing network into an advanced, cognitive and decentralized
infrastructure. The cognitive characteristic will be a viable choice for
future WSN. In this context the cognitive radio communication technique
is strongly needed for the implementation of smart WSN on the physical
system level dealing with information and communication technologies (ICT)
hardware and technical interoperability. The ICT ideas of cognition and
intelligence are required to make WSN smart, and to ensure their stability,
reliability, and security. The cooperative and self-organization aspect of
CONASENSE is the salient aspect of WSN of future that has to be deeply
researched.
Another important research area in the smart sensing is its greenness.
As the smart WSN of the future will be sustainable no need to say that
the automation process and the sensors communication and control in these
intelligent networks should be green as well. Therefore, there will be an
emergent need for developing energy efficient and green sensor technologies
that optimize power consumption even while guaranteeing a desirable quality
of service and a robust and secure communication/control performance. Green
ICT technologies will certainly be on the agenda for future research and
development of CONASENSE systems and networks.
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![1.3 Architecture 15
Currently compressed sensing is a rapidly emerging field of research.
Establishment of WSN in the light of mathematical theory of compressed
sensingisthestate-of-theart.Duetosparsityofthesensedsignals,properbases
are used for compressed sensing while satisfying the criteria for compressed
sensing. The promising achievements in this area are the reduction of number
of sensing elements and measurements, the reduction of the complexity of the
sensing method, optimized use of sensing power, and the optimized number
of sensing nodes [43].
1.3.3 e-Health
In view of rising costs in healthcare, increasing percentage of ageing pop-
ulation and the fact that many patients needing health-monitoring do not
necessarily require hospitalisation, one needs to look for new approaches for
the provision of low-cost (preventive) health services, especially for disabled,
elderly and chronically ill patients [44–45]. On the other hand, the progress
in ICT, biotechnologies and nanotechnologies accelerate innovations in the
field, and lead to miniaturization and large-scale production of efficient and
affordable products. Standardization that will ensure interoperability between
devices and information systems will open up the way for large-scale and
cost-effective deployment of e-health systems [46]. The CONASENSE may
therefore play a major role in the provision of e-health services, hence for the
QoL improvement.
Thanks to recent advances in sensor technology and networks, the human
health can be monitored by collecting data on specific physiological indicators
(e.g. blood glucose level, blood pressure, electrocardiogram and electroen-
cephalogram, portable magnetic resonance images, implantable hearing aid
etc.), via in-, on-, and/or out-body sensors. An electronic system is reported
in [47] that achieve thicknesses, effective elastic moduli, bending stiffnesses,
and areal mass densities matched to the epidermis. Unlike traditional wafer-
based technologies, laminating such devices onto the skin leads to conformal
contact and adequate adhesion based on van der Waals interactions alone, in
a manner that is mechanically invisible to the user. The system incorporates
electrophysiological, temperature, and strain sensors, as well as transistors,
light-emitting diodes, photodetectors, radio frequency inductors, capacitors,
oscillators, and rectifying diodes. Solar cells and wireless coils provide
options for power supply. This technology is designed and manufactured
to measure electrical activity produced by the heart, brain, and skeletal
muscles.
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![16 Vision on CONASENSE Architecture
Such systems typically perform sensing, data collection with user pro-
file information, including data aggregation, data visualization, and analy-
sis/alerting functions for the health professionals. The data, which is usually
collected at a hub, is periodically transmitted to a server through a gateway
(using IP). The database in the server may be used for preventative health
care, physiological/functional monitoring, chronic disease management, and
assessment of the QoL, e.g., fitness, diet or nutrition monitoring applications.
In view of the multiplicity and mobility of sensors and users, association of
the health monitoring data with patients requires serious consideration [48].
In e-health systems, the patients or sensing systems may update their data
in real time through Internet. Hence, the record of a patient becomes available
to authorized professionals anytime anywhere, for real-time monitoring and
intervention in emergency. Such systems also provide new forms of interaction
and coordination between health professionals and lead to novel scientific
approaches for medical applications.
E-health systems provide mobility to the patients via mobile health-
monitoring devices [49]. Patient mobility also calls for wearable, outdoor
and home-based applications. Physical and health conditions of patients
can be monitored in real-time using sensors observing the environment
and those that measure physiological parameters of the patient at home
and hospital environments. Similar approaches may be followed for the
safety of workers. Indoor positioning and tracking systems may be used in
hospitals, for example to track expensive equipment, and to guide patients
and health professionals inside the hospitals for more efficient and timely
services.
The health data can be stored on the sensor nodes and analyzed offline,
while emergency situations and reports may be made available to health
workers through a remote database. Hence, stored data from multiple patients
may be utilized for geographic and demographic analyses [50]. Mobility
solutions for wireless body area networks (BANs) for healthcare are already
available, through communications over low-power Personal Area Networks
(6LoWPANs) using Internet protocol Ipv6 [51]. These systems can provide
preventive healthcare, enhanced patient–doctor interaction and information
exchange. Continuous health-monitoring allows immediate intervention in
case of an emergency. Positioning, tracking and monitoring patients with
asthma, diabetics, heart disease, Alzheimer disease, obesity [52] as well
as visually impaired people, ambulance systems, small children, robotic
wheelchairs, pregnancy, blood pressure, artificial arms/legs, drug addiction
are believed to be important issues.
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![1.3 Architecture 17
Modelling the physical channel in body-area networks (BANs) is the
topic of intense research efforts [53]. Optimal use of relay nodes, adaptive
approaches for managing outages and retransmissions, cross-layer optimiza-
tion to share information between physical and media-access control (MAC)
layers will definitely improve the overall system performance. The MAC-
layer operation in BANs for e-health is addressed in the IEEE 802.15.6
draft standard for BAN [54]. For example, intra-body communication for
continuous-monitoringofpatientswithartificialheartembodiesseriousissues,
e.g., the operation of an antenna and the propagation of electromagnetic waves
in human body, which is a nonhomogeneous lossy medium. Similarly, reliable
signal transmission between sensors on the body under shadowing is still
among the areas of interest. Positioning with high precision in the human body,
which is strongly desired for surgical operations, is believed to be possible in
the near/mid-term.
The physiological data collected in e-health systems is bidirectional and
distributed through Internet and/or in heterogeneous networks to all interested
parties. The CONASENSE architecture should address the problems related
to protocol design, accuracy, reliability, data security, protection, privacy
of diagnoses, range, operation time, and interoperability between medical
devices [55–57]. These studies should be supported by databases, intelligent
decision support algorithms and programming languages. Recent efforts on
medical device interoperability resulted in a standard ISO/IEEE 11073 PHD
[58] for communications between health devices such as USB, Bluetooth, and
ZigBee.
CONASENSE architecture should also provide intelligent solutions
for wireless e-health applications including healthcare telemetry and tele-
medicine. Even the patients at some remote locations and/or unable to reach
a nearby health center may be monitored and managed; remote diagnosis
and emergency intervention can be accomplished by tele-medicine. Improved
and low-cost healthcare services may be provided to poor and geographically
remote patients by exploiting new technologies. In that context, such services
may provide a low-cost healthcare solution in less developed geographic
regions in the world.
Terrestrial and satellite segments of the CONASENSE architecture pro-
vide the deployment of interconnected integrated and interoperable telecom-
munications network for e-health applications. e-Health services are provided
by an Interactive Service Platform, including real-time audio and video
interactions among patients, specialists and health service providers. Both
citizens and physicians can access the interactive Service Platform from
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![18 Vision on CONASENSE Architecture
different locations (e.g. Health Points, Hospitals, Home) regardless of the
chosen access technology, either satellite or terrestrial. The Service Platform
will share health information among different applications and services (Self-
Care and Assisted). It is based on the Health Integration Engine (HIE):
this middleware guarantees the information exchange between the e-Health
subsystems Personal Health Media (PHM), Electronic Health Record (EHR),
Electronic Clinical Research Form (ECRF), Clinical Health record (CHR) and
the user access points.
1.3.4 Security and Emergency Services
Professional mobile radio (PMR) systems, e.g., APCO and TETRA, are
employed by police, fire departments, ambulance systems etc. for security and
emergency applications. Compared with ubiquitous commercial mobile radio
systems, these systems have some additional requirements for survivability
in disaster scenarios, operation in relay mode without needing base stations,
larger coverage areas (higher transmit powers) etc. Interoperability between
mobile radio and PMR systems is strongly desired. 4G systems may also
provide services to the PMR users via virtual private networks. Features like
relaying and survivability may be provided through diversity and coordination
between base stations. Incorporation of sensing capability and accurate time-
and positioning estimation in mobile radio systems may put them in a very
strong position for monitoring, and management of disaster, emergency,
mine-accidents, earthquake, fire-fighting, police patrolling, and intruder/fraud
detection. Rapid and accurate position estimation/navigation is very often
needed in military applications.
With accurate position estimation, a variety of applications and services,
suchaslocationsensitivebilling,andimprovedtrafficmanagementforcellular
networks may become feasible. Positioning of a mobile terminal is considered
to be critical for position-aware services such as such as E-911 in USA and
E-112 in European Union (EU) for emergency calls [59], [60]. Noting that
mobile-originated emergency calls are continually increasing and about 50%
of all emergency calls in the EU are originated by mobile users, location
estimation of a mobile user making an emergency call is strongly desired.
1.3.5 Traffic Management and Control
CONASENSE may also have a significant contribution in the domain of
traffic management and control. For example, monitoring and management
of highway/tunnel/bridge traffic which may need to be diverted, under
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![1.3 Architecture 19
congestion, to alternative itineraries may save valuable money and time and
reduce pollution. Intelligent transport systems (ITS) will significantly alle-
viate the urban traffic via inter-vehicular communications, communications
between the terminals along the roads, and broadcasting to vehicles the last-
minute traffic information. Controlling the distance between vehicles on the
road by onboard radars under rain/snow/fog is strongly desired [61–66]. Sim-
ilarly monitoring and navigation of the traffic in railways, harbors/ports/seas,
e.g., yachts, ships etc., air traffic (air traffic control and taxi) and UAV’s are
among the application areas of the CONASENSE. Monitoring and controlling
the border traffic between countries may also be used to prevent illegal
border crossings. Traffic control in shopping malls, banks, concert halls etc.
may be desirable for statistical purposes as well as for security reasons.
Concepts for traffic control, e.g., monitoring the migration paths, times and
the density of wild animals, could be valuable for the protection of wild life.
Similar arguments may be repeated for the monitoring of the farm animals. In
summary, CONASENSE architecture should provide intelligent and flexible
solutions in the area of traffic management and control.
1.3.6 Environment Monitoring and Protection
Rapid growth of the world population, high cost of transforming already
established and highly polluting manufacturing plants to become more
environment-friendly constitutes serious threats to our planet. Fortunately,
recent advances in CONASENSE-related technologies enable us to follow
more environment-friendly approaches at lower costs. Higher resolutions in
positioning and remote sensing is promising for monitoring and assessment of
earth resources, agricultural harvest, forests, seas, wild life, water resources,
weather/climate, ozone layer, electromagnetic and chemical pollution. The
CONASENSE architecture should address this problem, which is believed to
be increasing importance in mid- to far-terms, by integration of air-borne and
ground-based positioning and remote sensing platforms operating in various
frequency bands.
1.3.7 Smart Power Grid
Smart power grid modernizes the current electricity delivery system by
integrating ICT into generation, delivery, control and consumption of elec-
trical energy for enhanced robustness against failures, efficiency, flexi-
bility, adaptability, reliability and cost-effectiveness. In that sense, smart
grid embodies a fusion of different technologies where electrical power
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![20 Vision on CONASENSE Architecture
engineering meets sensing, ICT, positioning, control etc. [67]. The com-
munication protocols to be deployed for this purpose should modernize
and optimize the operation of the power grid and provide an accessible
and secure connection to all network users, especially for efficient use of
distributed energy sources [68]. Through communications between intercon-
nectedsensornodes,thesmartgridcontrolsequipmentandenergydistribution,
isolates and restores power outages, facilitates the integration of renewable
energy sources into the grid and allows users to optimize their energy
consumption.
Design of end-to-end QoS resource control architectures [69] and general
cyber-physical systems [61], efficient schemes for admission control, monitor-
ing/control of the smart grid and the fluctuations of the power load is believed
to be of prime importance for smart power grid networks [70]. Reliability and
security of integrated communication network of the Smart Grid should be
guaranteed in very adverse power line channels, which suffer high attenuation,
multipath, impulse noise, harmonics and distortion [71], and smart attacks
[72]. In addition to more reliable power line channel models [60], robust
modulation, coding, encryption [67], [72] and transmission techniques and
computational models are needed for optimized physical layer performance.
1.4 Conclusions
Emergence of enabling technologies and rapidly increasing demands for
services related to communications, sensing and navigation provides a good
opportunity for the integration of existing CONASENSE-related systems
and to design a novel flexible architecture so as to meet present and future
requirements. To achieve this goal, it is critical to identify the require-
ments for energy, terminal/platform and receiver/system design concerning
diverse application areas including e-health, security/emergency services,
traffic management and control, environmental monitoring and protection,
and smart power grid. Minimization of energy consumption and energy
harvesting deserve special attention in the novel CONASENSE architecture
design mainly because of requirements for mobility, high-data rate com-
munications and signal processing and green communications. The novel
CONASENSE architecture design should address problems and drawbacks
of the existing infrastructures/architectures and be sufficiently flexible for
future/potential developments. Consequently, the design of the CONASENSE
architecture should be carried out so as not only to integrate existing and novel
communications, navigation and sensing services but also to provide
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![References 21
smooth transition between existing and new systems in hardware and
software.
Acknowledgment
The authors would like to thank the CONASENSE WG2 Members Ernestina
Cianca, University of Rome, Prof. Ramjee Prasad, Aalborg University, Prof.
Enrico Del Re, University of Firenze, Prof. Vladimir Poulkov, University
of Sofia, Prof. K.C. Chen, National Taiwan University, Dr. Nicola Laurenti,
University of Padua, and Dr. Silvester Heijnen, Christian Huygens
Laboratories, for the fruitful discussions and their presentations during the
WG2 meetings which inspired the authors.
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Biographies
Mehmet Safak received the B.Sc. degree in
Electrical Engineering from Middle East Tech-
nical University, Ankara, Turkey in 1970 and
M.Sc. and Ph.D. degrees from Louvain Univer-
sity, Belgium in 1972 and 1975, respectively.
He joined the Department of Electrical
and Electronics Engineering of Hacettepe Uni-
versity, Ankara, Turkey in 1975. He was a
postdoctoralresearchfellowinEindhovenUni-
versity of Technology, The Netherlands during
the academic year 1975-1976. From 1984 to 1992, he was with the Satellite
Communications Division of NATO C3 Agency (formerly SHAPE Technical
Centre), The Hague, The Netherlands, as a principal scientist. During this
period, he was involved with various aspects of military SATCOM systems
andrepresentedNATOC3AgencyinvariousNATOcommitteesandmeetings.
In 1993, he joined the Department of Electrical and Electronics Engineering
of Eastern Mediterranean University, North Cyprus, as a full professor and
was the Chairman from October 1994 to March 1996. Since March 1996, he
is with the Department of Electrical and Electronics Engineering of Hacettepe
University, Ankara, Turkey, where he acted as the Department Chairman
during 1998-2001. He is currently the Head of the Telecommunications
Group.
He conducted and supervised projects, served as a consultant and orga-
nized courses for various companies and institutions on diverse civilian and
military communication systems. He served as a member of the executive
committee of TUBITAK (Turkish Scientific and Technical Research Coun-
cil)’s group on electrical and electronics engineering and informatics. He
acted as reviewer in various national and EU projects and for distinguished
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![2
Performance Analysis
of the Communication
Architecture to Broadcast
Integrity Support Message
Ernestina Cianca 1, Bilal Muhammad 1, Mauro De Sanctis 1,
Marina Ruggieri 1 and Ramjee Prasad 2
1CTIF Italy (University of Rome “Tor Vergata”)
2CTIF (Aalborg University, Denmark)
2.1 Introduction
Navigation capability is nowadays considered to be an assumed infrastructure
and the knowledge of position (or any function of it such as speed, acceleration
and heading) is nowadays fundamental to provide intelligent services for many
different reasons.
First of all, the service itself could be location-based, meaning that the
type of service to be provided and its configuration is dependent on the user
position. Furthermore, the knowledge of the position could be an important
element to optimize the design and performance of the other two key functions
that need to be performed to provide intelligent services, which are sensing
and communications [1]. For instance, the knowledge of the position of the
sensors nodes is important to optimize the efficient dissemination of data
through the sensor network (routing algorithms, or sleep/awake energy saving
mechanisms). In other cases, the knowledge of the position of the mobile
users could be used to optimize the communication protocols and the resource
usage; in a context where different radio access networks are available, the
knowledge of the position of the mobile terminals could be used to allocate the
resources or even predict the allocation within a heterogeneous Radio Access
Network (RAN) infrastructure. In the EU WHERE project for instance [2],
Convergence of Communications, Navigation, Sensing and Services, 31–50.
c
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![32 Performance Analysis of the Communication Architecture
the objective was to combine wireless communications and navigation for the
benefit of future mobile radio systems.
Nevertheless, the interaction between communication and navigation in
this chapter is considered from a different point of view: how a communication
infrastructure can be used to aid or to improve the performance of GNSS posi-
tioning systems? For instance, it is well known that a way to improve accuracy
and reliability of GNSS is by broadcasting GNSS corrections generated from
a network of ground stations (local, regional or global) to the user via various
data links, mostly 3G networks or communication satellites (i.e. EGNOS).
The Real Time Kinetic (RTK) or Precise Point Positioning (PPP) represents
two examples of this approach. The choice of the communication links has
an impact on the final performance of this augmented GNSS system. For
instance, GEO satellites such as EGNOS, encounters limitations in urban and
rural canyons, accentuated at high latitudes where the EGNOS GEO satellites
are seen with low elevation angles. Studies have been done to assess the
performance of EGNOS augmented GNSS for road applications [3].
Moreover, what is the impact on the communication network of the
added load due to the need to transmit those corrections? This question
could be important in future wide-area ITS services for urban users. Some
studies have been carried out recently to reduce this load by using proper
communication protocols and message format. Moreover, the performance
assuming for instance less-frequent update of this broadcast information
have been assessed in [4]. A communication infrastructure is needed also for
broadcasting information for integrity support.This issue is gaining increasing
attention and has not been deeply investigated yet. As it will be detailed in
the next Sections, so far most of the works have focused on the integrity
algorithm, assuming that the information contained in the so-called Integrity
Support Message (ISM) is available within the required time. However, it is
becoming increasingly important to better understand what is the impact of the
communication architecture infrastructure that will have to disseminate these
messages and what is the interaction between the format, content, frequency
of update of this information, with and the requirements and capability of
the chosen communication technologies. Some recent work has studied the
design drivers for the Integrity Support Message architecture [5] [6]. The
required size of ground monitoring networks, bounding methodology, and
Time to ISM Alert are among the ISM architecture design drivers. Equally
important is the dissemination network for the delivery of ISM to the final
user. The choice of dissemination network strongly affects the underlying
ISM architecture. In this Chapter we investigate the possibility to use TETRA
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![2.2 Integrity for Aviation Users 33
standard developed by the European Telecommunication Standards Insti-
tute (ETSI) [7] to disseminate ISM messages to Public Regulated Services
(PRS) aviation users. TETRA could represent a more robust (to jamming
and spoofing) and low cost communication technology for the distribution
of ISM to PRS users. We present preliminary results of end-to-end delay
to deliver short ISM latency message to the state aircraft using TETRA
network.
The Chapter is organized as follows: Section 2 presents the concept of
integrity for aviation users, the requirements and existing integrity provi-
sion architectures; Section 3 explains more in details the Advanced RAIM
algorithm for the provision of vertical guidance and presents possible ISM
contents, formats and dissemination networks; Galileo PRS services main
characteristics are presented in Section 4; TETRA standard and our proposed
ISM dissemination architecture are presented in Section 5 and 6; in Section 7
the performance in terms of latency of the proposed architecture are presented;
final remarks are drawn in Section 8.
2.2 Integrity for Aviation Users
Integrity is the measure of trust that can be placed in the correctness of
the information provided by the navigation system. It includes the ability
of the navigation system to provide timely alerts to navigation users when the
system must not be used for the intended period of operation. The navigation
system issues an alert within a given Time to Alert (TTA) when the error
in the position solution exceeds a predefined Vertical Alert Limit (VAL) or
Horizontal Alert Limit (HAL). In addition to integrity, other performance
metrics of a navigation system are the accuracy, continuity and availability.
The accuracy is the deviation of the estimated position solution from the
true position solution. The continuity of a navigation system is its capability
to perform its function without non-scheduled interruptions for the intended
period of operation. The availability is defined, as the fraction of the time
the navigation system is usable as compliance to accuracy, integrity, and
continuity requirements for a given phase of flight. The Required Navi-
gation Performance (RNP) for landing a civil aircraft [8] [9] is described
in Table 2.1.
The maximum probability of integrity failure or integrity risk defines the
probabilitythatthenavigationsystemdoesnotissuealerttothenavigationuser
within the given TTA given that the position solution exceeds the predefined
VAL or HAL. On the other hand, continuity risk defines the unexpected loss
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Convergence of Communications Navigation Sensing and Services 1st Edition Leo Ligthart
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- 3. Baudelaire and Freud Leo Bersani https://ebookultra.com/download/baudelaire-and-freud-leo-bersani/ Convergence of Mobile and Stationary Next Generation Networks 1st Edition Krzysztof Iniewski https://ebookultra.com/download/convergence-of-mobile-and-stationary- next-generation-networks-1st-edition-krzysztof-iniewski/ Weak Convergence and Its Applications 1st Edition Zhengyan Lin https://ebookultra.com/download/weak-convergence-and-its- applications-1st-edition-zhengyan-lin/ HRM in Europe Evidence of Convergence 1st Edition Chris Brewster https://ebookultra.com/download/hrm-in-europe-evidence-of- convergence-1st-edition-chris-brewster/ Emergence and Convergence Qualitative Novelty and the Unity of Knowledge Mario Bunge https://ebookultra.com/download/emergence-and-convergence-qualitative- novelty-and-the-unity-of-knowledge-mario-bunge/
- 5. Convergence of Communications Navigation Sensing and Services 1st Edition Leo Ligthart Digital Instant Download Author(s): Leo Ligthart ISBN(s): 9788793102767, 8793102763 Edition: 1 File Details: PDF, 11.07 MB Year: 2014 Language: english
- 6. Convergence of Communications, Navigation, Sensing and Services Editors Leo Ligthart & Ramjee Prasad River Publishers Series in Communications Convergence of Communications, Navigation, Sensing and Services, edited by Leo Ligthart, River Publishers, 2014. ProQuest Ebook Central, Copyright © 2014. River Publishers. All rights reserved.
- 7. Convergence of Communications, Navigation, Sensing and Services Copyright © 2014. River Publishers. All rights reserved.
- 8. RIVER PUBLISHERS SERIES IN COMMUNICATIONS Series Editor Prof. MARINA RUGGIERI Dr. H. NIKOOKAR University of Rome Tor Vergata Delft University Italy The Netherlands This includes the theory and use of systems involving all terminals, computers, and information processors; wired and wireless networks; and network layouts, procontentsols, architectures, and implementations. Furthermore, developments toward new market demands in systems, products, and technologies such as personal communications services, multimedia systems, enterprise networks, and optical communications systems. • Wireless Communications • Networks • Security • Antennas & Propagation • Microwaves • Software Defined Radio For a list of other books in this series, visit www.riverpublishers.com Copyright © 2014. River Publishers. All rights reserved.
- 9. Convergence of Communications, Navigation, Sensing and Services Editors Leo Ligthart Chairman CONASENSE the Netherlands Ramjee Prasad CTIF Aalborg University Denmark Aalborg Copyright © 2014. River Publishers. All rights reserved.
- 10. Published, sold and distributed by: River Publishers Niels Jernes Vej 10 9220 Aalborg Ø Denmark ISBN: 978-87-93102-75-0 (Print) 978-87-93102-76-7 (Ebook) ©2014 River Publishers All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, mechanical, photocopying, recording or otherwise, without prior written permission of the publishers. Copyright © 2014. River Publishers. All rights reserved.
- 11. Contents Preface ix 1 Vision on CONASENSE Architecture 1 M. Şafak, H. Nikookar and L. Ligthart 1.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.2 Requirements . . . . . . . . . . . . . . . . . . . . . . . . . 3 1.2.1 Requirements for Terminals/Platform . . . . . . . . 4 1.2.2 User Requirements . . . . . . . . . . . . . . . . . . 4 1.2.3 Technical Requirements for Receiver and System Design . . . . . . . . . . . . . . . . . . . . 5 1.2.4 Energy Requirements . . . . . . . . . . . . . . . . 6 1.3 Architecture . . . . . . . . . . . . . . . . . . . . . . . . . . 9 1.3.1 Positioning . . . . . . . . . . . . . . . . . . . . . . 11 1.3.2 Sensing . . . . . . . . . . . . . . . . . . . . . . . . 12 1.3.3 e-Health . . . . . . . . . . . . . . . . . . . . . . . 15 1.3.4 Security and Emergency Services . . . . . . . . . . 18 1.3.5 Traffic Management and Control . . . . . . . . . . . 18 1.3.6 Environment Monitoring and Protection . . . . . . . 19 1.3.7 Smart Power Grid . . . . . . . . . . . . . . . . . . 19 1.4 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . 20 Refereence . . . . . . . . . . . . . . . . . . . . . . . . . . 21 2 Performance Analysis of the Communication Architecture to Broadcast Integrity Support Message 31 Ernestina Cianca, Bilal Muhammad, Mauro De Sanctis, Marina Ruggieri and Ramjee Prasad 2.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . 31 2.2 Integrity for Aviation Users . . . . . . . . . . . . . . . . . 33 2.3 ARAIM . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35 v Copyright © 2014. River Publishers. All rights reserved.
- 12. vi Contents 2.3.1 ISM . . . . . . . . . . . . . . . . . . . . . . . . . . 36 2.4 Galileo Public Regulated Service (PRS) . . . . . . . . . . . 38 2.5 Terrestrial Trunked Radio (TETRA) . . . . . . . . . . . . . 39 2.6 Distribution of ISM Using Tetra . . . . . . . . . . . . . . . 40 2.7 Results and Analysis . . . . . . . . . . . . . . . . . . . . . 40 2.7.1 Simulation Environment . . . . . . . . . . . . . . . 41 2.7.2 Short Latency ISM- Range Domain . . . . . . . . . 41 2.7.3 Short Latency ISM- Satellite Domain . . . . . . . . 42 2.8 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . 42 Refereence . . . . . . . . . . . . . . . . . . . . . . . . . . 45 3 Nodes Selection for Distributed Beamforming (DB) in Cognitive Radio (CR) Networks 51 X. Lian, H. Nikookar and L. P. Ligthart 3.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . 51 3.2 DB for CR Networks . . . . . . . . . . . . . . . . . . . . . 55 3.2.1 Necessary Assumptions . . . . . . . . . . . . . . . 55 3.2.2 DB for CR Networks . . . . . . . . . . . . . . . . . 56 3.3 NS for CR Networks with Enlarged Main Beam . . . . . . . 59 3.4 Simulation Results of the NS Method . . . . . . . . . . . . 62 3.5 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . 67 Refereence . . . . . . . . . . . . . . . . . . . . . . . . . . 67 4 EEG Signal Processing for Post-Stroke Motor Rehabilitation 71 Silvano Pupolin, Giulia Cisotto and Francesco Piccione 4.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . 71 4.2 Neurophysiological Signal Analysis for Motor-Rehabilitation . . . . . . . . . . . . . . . . . . . 73 4.3 Neuroplasticity Enhancement and an Operant-Learning Protocol . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76 4.4 Constraints on Signal Processing to Implement an Operant-Learning Protocol . . . . . . . . . . . . . . . . 78 4.5 Preliminary Results . . . . . . . . . . . . . . . . . . . . . . 79 4.6 Conclusions and Future Goals . . . . . . . . . . . . . . . . 84 Refereence . . . . . . . . . . . . . . . . . . . . . . . . . . 85 Copyright © 2014. River Publishers. All rights reserved.
- 13. Contents vii 5 Quality Improvement of Generic Services by Applying a Heuristic Approach 91 Oleg Asenov, Pavlina Koleva and Vladimir Poulkov 5.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . 91 5.2 Service Systems without Service Element Blocking . . . . . 92 5.3 Dynamic Association as a Management Approach . . . . . . 98 5.4 Characteristic Model of the Servicing Properties of the Non-blocking Servicing Elements . . . . . . . . . . . 100 5.5 Heuristic Algorithm for Dynamic Association of Asynchronous Requests . . . . . . . . . . . . . . . . . . 108 5.5.1 Formulation of the Problem for Finding a Generalized P-median Set as a Linear Programming . . . . . . . 109 5.5.2 ADD/DROP Heuristics Algorithm . . . . . . . . . . 111 5.6 Example of Application of ADD/DROP Heuristics for Solving the Cascade Problem of Hierarchically Connected Sets . . . . . . . . . . . . . . . . . . . . . . . . 114 5.7 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . 120 Refereence . . . . . . . . . . . . . . . . . . . . . . . . . . 123 6 Machine-to-Machine Communications for CONASENSE 127 Kwang-Cheng Chen and Shao-Yu Lien 6.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . 127 6.2 Wireless Infrastructure . . . . . . . . . . . . . . . . . . . . 127 6.2.1 Ubiquitous Connections via 3GPP Heterogeneous Network (HetNet) Architecture . . . 129 6.2.2 D2D Empowered Group Based Operations of MTC Devices . . . . . . . . . . . . . . . . . . . 131 6.2.3 Cognitive Operations of MTC Devices . . . . . . . 132 6.2.4 The QoS Guaranteed Optimal Control for Cognitive Operations of MTC Device . . . . . . 135 6.3 Statistical Networking in Machine Swarm/Ocean . . . . . . 137 6.3.1 Sensing Spectrum Opportunities for Dynamic Spectrum Access . . . . . . . . . . . . . . . . . . . 139 6.3.2 Connectivity of Spectrum Sharing Wireless Networks Under Interference . . . . . . . . . . . . . 143 6.3.3 Routing in Cooperative Cognitive Ad Hoc Networking . . . . . . . . . . . . . . . . . . . . . 148 Copyright © 2014. River Publishers. All rights reserved.
- 14. viii Contents 6.3.4 Statistical Control of QoS and Error Control . . . . . 150 6.3.5 Heterogeneous Network Architecture . . . . . . . . 152 6.3.6 (Information Dynamics and) Traffic Reduction and In-Network Computation . . . . . . . . . . . . 153 6.3.7 Nature-Inspired Approaches toward Time Dynamics of Networks . . . . . . . . . . . . . . . 156 6.4 Energy-Efficient Implementation, Security and Privacy, Network Economy, Deployment and Operation . . . . . . . 157 6.4.1 Application Scenarios of M2M System . . . . . . . 157 6.4.2 Energy Harvesting Communication Networks . . . . 158 6.4.3 Security and Privacy . . . . . . . . . . . . . . . . . 160 6.4.4 Spectrum Sharing Network Economy . . . . . . . . 161 6.4.5 Implementation, Deployment, and Sustainable Operation . . . . . . . . . . . . . . . . . . . . . . . 162 6.4.6 Toward the Reference Model of M2M Communication Architecture . . . . . . . . . . . . . 164 6.5 Concluding Remarks . . . . . . . . . . . . . . . . . . . . . 165 Refereence . . . . . . . . . . . . . . . . . . . . . . . . . . 165 7 Maximizing Throughput in Chip to Chip Communications 181 Hristomir Yordanov, Albena Mihovska, Vladimir Poulkov and Ramjee Prasad 7.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . 181 7.2 Antenna Implementation and Challenges . . . . . . . . . . . 182 7.3 Area-Efficient Antennas . . . . . . . . . . . . . . . . . . . . 184 7.3.1 Antenna Structure and Radiation Mode . . . . . . . 184 7.3.2 Interference Issues . . . . . . . . . . . . . . . . . . 188 7.3.3 Substrate Losses . . . . . . . . . . . . . . . . . . . 192 7.4 Chip-to-Chip Communication . . . . . . . . . . . . . . . . 194 7.5 Maximizing the Throughput . . . . . . . . . . . . . . . . . 195 7.6 Conclusion . . . . . . . . . . . . . . . . . . . . . . . . . . 196 Refereence . . . . . . . . . . . . . . . . . . . . . . . . . . 197 Index 201 AppendixA 203 Copyright © 2014. River Publishers. All rights reserved.
- 15. Preface The CONASENSE foundation was established as brain tank in November 2012. Main aim is to define and steer processes directed towards actions on investigations, developments and demonstrations of novel CONASENSE services with high potential and importance for society. Characteristic for realizing the services is that integration of communications, navigation and sensing technology is needed. The horizon for new services is 2020 and beyond. Knowing that CONASENSE can play a role in a wide range of areas we decided to limit ourselves in the initial phase 2012–2015 to 2 areas with 2 respective working groups : • Quality of life (QoL) • Integrated CONASENSE Architectures (ICA) Most members of the working group are connected with academia, but all have strong links with non-academic organizations, governmental and non-governmental institutes as well as industries. Some members come from semi-governmental organizations and industry. It is foreseen that the number of participating organizations will expand in 2014 and beyond. The year 2013 was very successful for CONASENSE. We published the 1st CONASENSE book.Several articles for the CONASENSE journal have been written, reviewed and edited.Another highlight was the 2nd workshop in March 2013, followed by intensive discussions on the CONASENSE essence, that is: • Giving contents to interconnections between communications, naviga- tion, sensing and services • Stimulating cooperation with multi-disciplinary groups active in tech- nology and in development of services as well as for user groups implementing and evaluating new services • Developing roadmaps for novel services • Preparing proposals for activities which have impact on governments and decision makers CONASENSE was introduced in USA, China and Indonesia. ix Copyright © 2014. River Publishers. All rights reserved.
- 16. x Preface This 2nd CONASENSE book is based on the brainstorms during the workshop in March 2012 followed by communications between authors and editors. At the occasion of publishing the book I thank firstly the authors of the book chapters. Secondly I thank the participants in the working groups for their input and discussions on the essence of CONASENSE. Special thanks go to Silvano Pupolin for his duties in the QoL working group and to Mehmet Safak and Ernestina Cianca for their efforts in the ICA working group. This 2nd CONASENSE book reflects some most interesting examples of QoL and ICA activities which will play a role in future CONASENSE initiatives. I conclude with the same sentence written in my preface of the 1st CONASENSE book: “I hope that readers of the book are inspired by the topics that need future research and development and that they become motivated to work on those CONASENSE topics and finally that they are eager to join CONASENSE community”. Leo Ligthart Chairman CONASENSE www.conasense.org Copyright © 2014. River Publishers. All rights reserved.
- 17. 1 Vision on CONASENSE Architecture M. Şafak,1 H. Nikookar2 and L. Ligthart3 1University Hacettepe, Turkey 2Delft University of Technology, The Netherlands 3Chairman Conasense, The Netherlands 1.1 Introduction Recent advances in digital communications and high-speed digital signal processing led to innovative technologies, techniques, systems and services in the areas of communications, navigation and sensing. Supported by the integrationoftransmissionofvoice,dataandvideousingInternetProtocol(IP) and the accompanying increase in the demand, these changes greatly improved the versatility, availability and ubiquitous use of these services. Nowadays, we observe a rapidly increasing demand and innovative application areas for ser- vices related to positioning, tracking and navigation of some users/platforms. For example, we currently use available services for determining and tracking the position of a user in mountainous/forest areas or in seas, for finding the address of a colleague that we want to visit as we drive in a large city or learning the status of a parcel in a postal service. Similarly, we observe an unprece- dented development in sensing technology, sensors and sensor networks. A variety of sensor types are now available on the market in many domains, from tasting the quality of wine/tea/coffee to determining the temperature, the humidity and the mineral and water content of the ground for agricultural pur- poses,sensing/monitoringthephysiologicalconditionsofdrivers/patientsetc.. Sensors operate at various frequency bands and locations, e.g., indoor/outdoor, airborne, space-borne, terrestrial, underwater and underground. Traditional approaches may not be optimal for the integrated provision of these services, because of the allocation of different frequency bands, waveforms and hence different receiver platforms for these services. For example, navigation signals generally contain information about the platform Convergence of Communications, Navigation, Sensing and Services, 1–30. c 2014 River Publishers. All rights reserved. Copyright © 2014. River Publishers. All rights reserved.
- 18. 2 Vision on CONASENSE Architecture identity/location and the time. In addition, sufficiently large bandwidths are allocated to navigation services so as to allow accurate position determination and transmission/reception of navigation signals. Similar arguments may be repeated for communication and sensor systems. In view of this and the fact that modern telecommunication systems support very high data rates, strongly needed integration of digital COmmunications, NAvigation, SENsing and related Services (CONASENSE) looks feasible (see Figure 1.1). The technol- ogy is believed to be available for the integration of CONASENSE-related ser- vices under realistic scenarios. The emphasis of the CONASENSE Initiative [1], [2] is on the improvement of the quality of life (QoL) of human beings in harmony with the environment using the available and enabling technologies. The CONASENSE mission also includes helping the development of innova- tive technologies for mid- to far-terms. The QoL is believed to be improved when human beings can choose freely between sufficiently many user-friendly CONASENSE services which do not compromise the user-privacy. Covering a large domain of research, the CONASENSE has a high potential for a variety of applications and service provision to a large spectrum of users. Consequently, the CONASENSE-related studies may be research- oriented, e.g., related to system architecture, performance evaluation, protocol design, physical layer techniques etc.; application-oriented, e.g., proof-of- concept studies, system or prototype development; and/or service-oriented, including approaches for the provision of a multitude of services. These services may be related to, for example, health, monitoring and protection of the environment, traffic-control and security. Figure 1.1 The CONASENSE framework Copyright © 2014. River Publishers. All rights reserved.
- 19. 1.2 Requirements 3 Section 2 will present the requirements for present and future CONASENSE services. Section 3 will provide architectural considerations related to the CONASENSE-related technologies and services with emphasis on areas including e-Health, security, traffic control, environment monitoring and protection. The CONASENSE architecture aims to specify how the infrastructures related to communications, sensing and navigation should interact so as to provide the desired QoLservices.Architectural considerations will be presented for the evolution of CONASENSE services with time even though long-term predictions may not be easy. The problems and drawbacks of the current infrastructures and architectures will be reviewed, and backward compatibility issues will be briefly discussed. 1.2 Requirements QoL improvement by developing novel CONASENSE systems requires strategy for and design of integrated architecture that meets the technical requirements at system level and for all interfaces (terminals, equipment, person to machine, M2M [3–5]) as well as technical requirements for receiver and system design. Hence, integrated synergistic use of CONASENSE- capabilities is mandatory. Flexible, intelligent, and heterogeneous architecture of the system must operate with any kind of enabled devices (i.e., fixed, portable and handheld ones) and control centers, and the services must be provided by, amongst others, satellite and terrestrial segments. The use of advanced cognitive, cooperative and context− and location-aware tech- nologies and distributed system intelligence and application programmable interfaces (API) are strongly desired. The architecture should be intelligent with sensing, learning, decision and action functions, with the exploitation of the benefits of clouds of users; reconfigurable, adaptive, energy efficient; high efficiency, capacity satisfying QoS requirements; support security demands; incorporate context awareness; integrate available technologies and provide the optimization of the architecture for various applications. The middleware should integrate all heterogeneous components (localization, communication and sensing) in a common stratum to implement the basic functionalities for all the services. On top of the middleware the applications should provide the complex system intelligence functionalities. QoL improvement can be fastened via multi-disciplinary academic and applied research, which requires international institutional cooperation and the presence of test laboratories with state-of-the-art test and measure- ment equipment. Main criterion for developing novel CONASENSE system Copyright © 2014. River Publishers. All rights reserved.
- 20. 4 Vision on CONASENSE Architecture demonstrators is that major user organizations indicate the utilization poten- tials for solving problems in Society and in QoL in particular. Those system developments should be selected which require latest (and new) insights in basic and applied technology and which bring clear visions on “selling attributes”, like needs for introducing the system in applications, potential market expectations etc. Feedback on CONASENSE initiatives need to be solicited from user organisations, industry and governmental innovation bodies so as to facilitate fund raising. Below is presented a brief description of the requirements about the CONASENSE-related services from different perspectives. 1.2.1 Requirements for Terminals/Platform Users,transceivers,andplatformstobenavigated,andtargets/parameterstobe sensed in-situ or remotely may be listed as space-borne (satellites, unattended aerial vehicles (UAVs), high-altitude platforms), sea-borne, ground-based, underground (earthquake, mines, tunnels etc.), underwater (communica- tions, vehicle navigation, etc.), isolated places (mountains, forests, seas, oceans, deserts), indoor/outdoor, live tissues etc. For example, space-borne telescopes are already being used successfully in radio astronomy. Near- earth orbiting satellites are used in many areas such as remote-sensing, harvest prediction, surveillance and environmental protection. Sensing and telecommunications may also be used for safety purposes, e.g., monitor- ing disaster and underground mines and tunnels. Similarly, underwater communications, sensing and navigation may have numerous application areas, including navigation of underwater platforms, remote sensing wild life in the seas/oceans/deserts, fishing industry, mineral exploration in the oceans and monitoring and protection of the environment. Similarly, posi- tioning and navigation applications are rapidly increasing in many areas of medicine. The CONASENSE architecture should fulfill the above-listed requirements. 1.2.2 User Requirements The requirements for CONASENSE-related services are mainly related to the user mobility and the environment. The users would prefer to have low-cost, light-weight, user-friendly, and low power/energy consuming receiving ter- minals, operating at all/most frequency bands allocated to the CONASENSE- related services with optimized coverage. Availability of these services may impose stringent requirements, e.g., the availability of navigation services Copyright © 2014. River Publishers. All rights reserved.
- 21. 1.2 Requirements 5 might be of vital importance in certain scenarios. The privacy and surviv- ability may be required for many services. The cognition, self-organization capability and adaptability of the terminals against different environmental and operational conditions are strongly desired. In addition to all these, these services must be ubiquitous, reliable and affordable. 1.2.3 Technical Requirements for Receiver and System Design The frequency bands allocated to CONASENSE services differ depending on the particular application. Consequently, the propagation channels behave differently and the requirements for transceiver design are not the same. Depending on the applications and the related services, the operating fre- quency bands may cover radio frequency (RF), optical, infrared (IR), acoustics etc. A common (integrated) and interoperable receiver for CONASENSE services is required to operate at different frequency bands, transmit power levels, receiver sensitivities, antenna structures, single- and multi-carrier transmissions techniques and modulation schemes [6–9]. Improved position- ing accuracy by integration of the navigation data collected from different sources, such as global positioning system (GPS), Galileo, GLONASS, Wi-Fi, gyroscopes, accelerometers etc., is strongly desired. Software-defined radio (SDR) may be considered as a strong candidate for an integrated receiver. Present technologies allow the design of agile front-ends with frequency synthesizers of fast hopping and settling times and with low phase noise. Followed by fast analog-to-digital and digital-to-analog convertors, the present signal processing technology facilitates the design of common low-noise and sensitive SDR receivers, by using a DSP chip, ASIC or FPGA, operating at numerous frequency bands and interoperable with dif- ferent systems [10], [11]. A multi-band SDR for spaceborne communications, navigation, radio science and sensors is reported to support communication, command and telemetry links, high-rate scientific data return links and two- way Doppler navigation. Modularity within core hardware and firmware platforms allow for additional software and software upgradeable features, technology enhancements and implementations with minimal non-recurring engineering costs [12], [13]. In view of the above, system architecture design which would enable integrated CONASENSE services is a challenging task. One of the first issues to be resolved in this context concerns the interoperabil- ity with LTE/4G, professional mobile radio (PMR) and/or terrestrial and satellite-based navigation systems [13]. In view of the anticipated diverse Copyright © 2014. River Publishers. All rights reserved.
- 22. 6 Vision on CONASENSE Architecture applications, direct communications and multi-hop relaying between different user equipment without using base stations may also be required. Other issues to be concerned include broadcasting, multicasting, security, routing, radio resource management, efficient power/energy consumption, network establishment etc. 1.2.4 Energy Requirements Energy is a valuable resource in CONASENSE-related applications. Design of battery- or electricity-operated wireless communications and sensor nodes are based on continuous flow of power from the energy/power source to the electronic equipment. If electricity or battery is not available on-site, the systems may be operated by harvesting energy from their environment. Energy harvesting implies the collection of energy from ambient sources and converting into electrical energy. However, irrespective of whether the required electric energy is provided by the mains, the battery or energy harvesting, minimization of the consumed energy is strongly desired because of reasons such as cost, equipment life-time, electromagnetic compatibility and for future innovative applications [14]. From an energy perspective, a communication or a sensor node may be considered to be composed of supply and demand sides. A sensor node differs from a communication node mainly by the presence of a sensor. The demand side consists of energy consuming units such as a sensor, a signal processing unit, a wireless transceiver and a buffer, either to store the sensed data or the data to be transmitted/received [15], [16].Transceivers typically use Bluetooth or Zigbee protocols to communicate within a range of maximum 30 m and require output power levels in the order of 2–100 mW. Hence, power levels needed by a sensor node may be in the order of few 100 mWs including all components. The supply side of a node consists of energy storage and energy harvester in energy harvesting systems. Using the harvested energy and/or the battery, it communicates via its transceiver with outside world; it receives orders from and transmits the sensed data to its base station. The lifetime of energy harvesting systems is theoretically infinite. Wirelesssensornodesareusuallybattery-operatedbecauseofthedifficulty and/or inconvenience of reaching sensor nodes in remote locations, high cost of maintenance and replacement. Hence, the energy efficiency determines the life-time of battery-operated sensor nodes, which are required to provide independent, sustainable and continuous operation. Battery-operated nodes do not have an energy harvester and the node life-time is limited by the battery Copyright © 2014. River Publishers. All rights reserved.
- 23. 1.2 Requirements 7 capacity. Recently remarkable improvements are observed in power density (W/kg), efficiency, amount of supplied power and the capacity (Amp.-hour) in the area of energy storage [17]. Nevertheless, operation by batteries still has its limitations and may not be suitable for certain applications. Hence, there is strong demand for energy harvesting systems that can generate their own energy from their environment. Since energy harvesting may not always be available and predictable, energy harvesting systems employ batteries for storing the harvested energy for present/future use. In this respect, the harvesting efficiency and the availability of energy source are the fundamental issues to be considered. Since the present designs are presently based on the continuous flow and ever-presence of the electric energy, these nodes may not operate optimally with energy harvesting and a novel approaches are required for designs with energy harvesting. Therefore, energy harvesting nodes should be designed so as to account for the limitations due to scarcity, non-uniform flow and limited-availability of power in some time intervals which cannot be predicted beforehand. The CONASENSE architecture should allow for energy harvesting in mid- to far-terms. 1.2.4.1 Intelligent Designs for Self-Powered (Energy Harvesting) Nodes Classical design of sensor/communication nodes is based on the availability of a continuous flow of a constant power level (infinite energy) to the demand side. On one hand, dramatic reductions are strongly desired in power/energy levels dissipated on the demand side of existing wireless nodes. The energy consumption in transceivers may be decreased by reducing the data to be transmitted using source coding, choosing adaptive channel coding and modulation strategies, using efficient transmission scheduling, exploiting power saving modes (sleep/listen) and using energy efficient routing and medium access control [18], [19]. On the other hand, energy harvesting technology is presently far from satisfying present needs. Energy sources may be (un)controllable and/or (un)predictable for energy harvesting; solar energy is predictable but uncontrollable, while RF energy harvesting in a RFID system may be controllable and predictable at the same time. Therefore, limited power/energy that can be harvested sets a constraint on the average power or energy consumed by the demand side for self- powered operation.This implies that energy harvesting, storing and processing technologies should be improved so as to help sustainable and continuous operation. Copyright © 2014. River Publishers. All rights reserved.
- 24. 8 Vision on CONASENSE Architecture Even if infinite energy becomes available to the supply side, energy generation may not be continuous and/or rate of generation may be lim- ited. Storing the harvested energy may partially alleviate this problem since it may regulate the power flow. Nevertheless, electronic devices with classical design cannot reliably operate under these conditions. Therefore, energy generation profile of the supply side should be matched to the energy consumption profile of the demand side. This requires a system- level approach involving variation-tolerant architectures, ultra-low voltage and highly digital RF circuits. In addition, one needs DSP architecture and circuits which are energy-efficient, energy-scalable, and robust to vari- ations in the output of the supply side. Energy-scalable hardware may call for techniques for approximate processing, which implies a trade-off between power and arithmetic precision [20]. In wireless sensor networks, the demand side may be designed with sleep/awake periods in synchronism with energy harvesting by the supply side. Energy consumption policy may be optimized in seeking a tradeoff between the throughput and the life- time of the sensor node [21]. Such approaches are believed to result in more than an order of magnitude energy reduction compared to present systems [22]. In some projects like Pico Radio (Berkeley), μAMPS (MIT), WSSN (ICT Vienna) and GAP4S (UTDallas), densely populated low-cost sensor nodes are foreseen to operate with power levels of approximately 100 μW; such power levels is believed to be within the capabilities of energy harvesting. Even though dramatic improvements are still needed, rapidly-evolving energy har- vesting technologies are believed to be promising for self-powered operation. The CONASENSE architecture in the mid- to long-term should address the energy harvesting problem especially in the mobile communication platforms and wireless sensors. The use of nanogenerators is foreseen to be used for a variety of applications including intra-body drug delivery, health monitoring, medical imaging, environmental research (air pollution control), military applications (surveillance networks against nuclear, biological, and chemical attacks at nanoscale, and home security), and very high data rate communications. Energy harvesting may enable the widespread use of the nanotechnology [23]. In addition to energy harvesting, the energy problem may be alleviated by using cognitive approaches and distributed and cooperative data process- ing among communication and sensor nodes. Beamforning in WSN also needs to be considered for CONASENSE architectures with reduced energy consumption. Copyright © 2014. River Publishers. All rights reserved.
- 25. 1.3 Architecture 9 1.3 Architecture The CONASENSE architecture is required to satisfy the requirements listed above. In this context, a flexible and modular platform integrating CONASENSE-related services should be able to address a wide range of QoL applications. Such a complex platform operating in different frequency bands/channelsandfornumerousapplicationsshouldbeuser-friendly,energy- efficient and able to operate at different transmit/receive power levels using adaptive modulation/coding and transmission techniques. MIMO techniques, wavelets and ultra-wideband may be considered to render the CONASENSE architecture more flexible. User-friendliness is an important issue for improv- ing the QoL of users of all ages with different needs and education levels. Priority of services and users are thought to be essential in complex platforms. The security is important not only for navigation, location finding and positioning, but also for sensing and telecommunications. Therefore, the CONASENSE architecture design should also satisfy mid- and far-term security requirements in a user-friendly way without compromising the system performance. Similarly, reliability in normal operations and safety in case of abnormal events and emergency situations should be provided by the architecture. On the other hand, in present day as well as in the mid- and far-terms, the user privacy will definitely be an essential requirement for the QoL. Some aspects of sensing (medical, biological) may require higher degrees of privacy compared to others. The privacy issue should be tailored and controlled by the user, since it can change depending on user needs and specific applications/situations; hence architecture designs providing flexible privacy degree controlled by the user should be sought. The architecture should be flexible enough so as to allow the introduction of cognition into the system as new technological developments permit it, especially in mid- to far-terms. The cognitive elements inherent in the integrated system architecture should enable the system to be adaptive and leading to optimized decisions in quasi-real-time according to the user type, channel conditions and applications. In this respect, heuristic approaches for quality improvement of generic services may help the architecture to minimize the time for data collection, signal processing and decision making as well as to allow a trade-off between the optimality of the decisions and the required computational complexity. The architecture should be open so as to ease the introduction of new services/applications as much as possible. Copyright © 2014. River Publishers. All rights reserved.
- 26. 10 Vision on CONASENSE Architecture Since the anticipated architecture will operate with various communi- cation, navigation and sensor systems at different frequency bands and in different channels, the operation and/or coexistence in the mid-term with IP should be carefully considered. One should as well consider the feasibility of new network protocols for long-term architectural studies. User-centric archi- tecture should account for the evolution of large numbers of CONASENSE services with time. One needs to carefully consider the optimization of the architecture vis-à-vis the CONASENSE services and whether layerless communications lead to an improved architecture at least for the provision of some selected services. The integration of CONASENSE functionalities by means of hetero- geneous and reconfigurable networks is a breakthrough for the growth of distributed cloud computing and social interaction technologies and a big leap towards the provision of a plurality of services and applications, ideally and in perspective a universal library of services seamlessly provided to users. In the sub paragraphs below various services will get attention: positioning, sensing, e-health, security and emergency services, traffic management and control, environment monitoring and protection, smart power grid. Such new services can improve the QoL of users. The services related to e-health and emergencyfieldsareexemplaryapplications,whereflexible,multi-serviceand cooperative heterogeneous architectures play a fundamental role. The integra- tion of CONASENSE functionalities in a heterogeneous, flexible, cooperative system is far from being presently available. Design, implementation and deployment of this visionary scenario to provide better services to the third- millennium users is indeed one of the most challenging issue for the scientific community. For economic and technical considerations, a modular CONASENSE system architecture is strongly desired, meaning that each system is com- posed of a series of sub-systems in hardware and/or software. Compa- rable to “SDR”, the basis for novel CONASENSE systems may follow a “software-defined-CONASENSE” approach. It should lead to set up a set of standards at the interfaces so that integrated system developments, functionality, and performance can first be tested in software. Embodied software-defined functionalities and on-line testing performance may be specified in order to meet the overall system specifications at system and sub-system levels. The tests can be made even before hardware developments start, but also during various phases of the (sub-) system developments. Different technological institutes may take the responsibility for the progress and development for the specifications, acceptance, integration and technical Copyright © 2014. River Publishers. All rights reserved.
- 27. 1.3 Architecture 11 testing of different sub-systems while some others assume the responsi- bility for performance testing of the integrated system and user interface performance. Novel architecture design approaches should be jointly considered with backward compatibility issues since new systems need to be integrated with the existing ones. Similarly, horizontal integration is also needed between networks for communications, navigation and sensors. Potential architecture solutions should also be based on trade-offs between the cost and innovative content. Efforts for modeling the architectures facilitate the comparison of both existing and proposed architectures in order to determine sources of technical challenges in implementation and facilitate the estimation of the implementa- tion and operational costs. Risk assessment evaluations are also necessary. Developing a figure-of-merit help enabling the quantitative evaluation of each architecture and operational process option. Modular system designs, approches for system operation as well as software and hardware fixes and maintenance should be should be carefully considered [24]. 1.3.1 Positioning Positioning, location finding and navigation plays a crucial role in CONASENSE applications. Accurate, reliable and real-time positioning is a serious issue in the operation of location-aware services, e.g., in the formation and self-organization of ad hoc networks [25], in navigation and sensing [26], emergency conditions etc. Existing positioning systems have different waveforms, operational fre- quencies and capabilities. In addition, different frequency bands are allo- cated to navigation, communications and sensing systems. Therefore, the CONASENSE architecture should optimize data collection and decision making in central or distributed ways for improved positioning accuracy. The recent advances in positioning techniques is believed to improve the position- ing accuracy in indoor and outdoor environments and pave the way for many innovative CONASENSE applications even in the near future. Recent tech- nological developments e.g. in micromechanical systems (MEMS), enables the development of gyroscopes and accelerometers at smaller sizes to be incorporated in mobile terminals. Similarly, the use of multiple-input multiple- output (MIMO) techniques is expected to improve not only the performance of the communication systems but also help for accurate position and time estimation. Intense research efforts are going on for the integrated design of Copyright © 2014. River Publishers. All rights reserved.
- 28. 12 Vision on CONASENSE Architecture navigation systems for improved time and position estimation. Telecommu- nications, sensing and navigation communities are interested in bio-inspired algorithms [27] for improving the performance of CONASENSE-related ser- vices. Evolution-perfected bio-algorithms for colony life, migration of fishes, bees [28], ants, birds and herds inspire the scientists to exploit bio-inspired algorithms more aggressively. Positioning systems are usually categorized as network-based or mobile- based depending on the location where position calculations are per- formed. Calculations for position estimation may be mobile-based, when the positioning information is extracted from the received signals, or network- based if information collected through reference terminals is processed at a central unit. Positioning systems may be either terrestrial-based and used for both outdoor and indoor environments, or satellite-based, which offer global coverage but generally serve to only outdoor users. Satellites can play a leading role in CONASENSE services due to their immunity against ground-based catastrophic events and for their ability of col- lecting information created by sensors deployed on the surface of the earth and the sky, if necessary. They can provide communications, sensing and enable assisted localization, combining information from positioning satellites and terrestrial terminals. Efficient architecture design of hybrid terrestrial-satellite positioning systems and their integration with communication systems is a challenging problem. Multiband receiver antennas are needed for operation in the frequency bands allocated to navigation, sensing and communication systems. Transmit antennas should be designed so as to produce signals with isotropic power spectral density within global coverage for navigation receivers [29]. Indoor positioning, integration of positioning with payment systems, positioning in live tissues, e.g., in human body, underwater positioning, positioning in tunnels, positioning of chemical pollutants in the air are among the numerous areas to be discovered. 1.3.2 Sensing Recent advances in digital technology enabled the development and pro- duction of high resolution, low-power, environment-friendly, long-life, low- cost and small-size sensors [30], [31]. Consequently, we observe in our everyday life various sensor types, including RFID-, MEMS-, biometric-, acoustic-, video-sensors and so on. Sensors are used in a very large spectrum of applications, including health monitoring [32], [33], underwater acoustic Copyright © 2014. River Publishers. All rights reserved.
- 29. 1.3 Architecture 13 networks [34], smart grid applications [35], agriculture [36], emergency applications, automotive industry [37] etc. Therefore, applications related to sensingwilldefinitelyhaveanincreasingimportanceinCONASENSE-related applications. Sensors may be used for sensing locally or remotely; the information collected by the sensed signals may be processed in situ, in a distributed fashion, or at a fusion center [38], [39]. Multiple sensors may be employed for cooperative sensing when the data collected by a single sensor does not meet the requirements. Data collection, processing and management architecture and techniques, e.g., sensor fusion, data fusion and/or information fusion, and making an optimum multi-criteria decision concerning the sensed data, need to be carefully considered in the design of the CONASENSE architecture. Heterogeneous networks of sensors may be remotely located from each other and operate at different frequency bands. For example, in a mar- itime environment, there are various technologies for detection and locating objects such as coastal radar, sonar, video camera, IR, automatic identifi- cation system, automatic vessel locating. In addition, these signals should be processed with HF communications, intelligence data etc. Moreover, centralized or decentralized fusion of the information provided by vari- ous sensors may be required to ensure reliable performance for handling complex scenarios due to temporary loss of availability, error, limits of coverage etc. A multi-sensor tracking and information fusion methodol- ogy /architecture is needed to harness the effectiveness of multiple sensor information [40]. Recent research efforts on electronic nose, electronic eye and electronic tongue lead to versatile and innovative applications. Sensing and monitoring volatile organic compounds, atmospheric pollution, hazardous gases, chem- icals and explosives may be cited among the applications for security and environmental protection. In health-related applications, one may cite the diagnosis of lung cancer at early stage, identification of urinary tract infection and helicobacter as well as detection, discrimination and monitoring of drug, drug users and smokers. Sensor systems are also used for building artificial nose, tongue and eye for robots and other applications as cited in the literature [41], [42]. A remarkable area that has to be emphasized in the future CONASENSE applications is the amount of data exchanged in the wireless sensor networks (WSN). The data across all levels of the network may be generated by smart sensing systems, supervisory control and data acquisition systems, wide area monitoring systems, and other sensing/monitoring devices. The huge amounts Copyright © 2014. River Publishers. All rights reserved.
- 30. 14 Vision on CONASENSE Architecture of data and information need to circulate and be stored among control centers, devices and users. Therefore, the use of data compression techniques will be desirable to help mitigating the burden of the communication among CONASENSE sensors and control systems. To this end, the information acquired by the sensors should be compressed at the sending terminals as much as possible, before sending through the wireless communication system. The compression should preserve the valuable information con- tained in the data, and the compressed data- when received at receiving terminals- should be perfectly reconstructed too for analysis. In this regard, the Wavelet technology for data compression is of paramount importance [43] for the future CONASENSE applications. With this technology data can be compressed before it is sent out in order to mitigate the data congestion in the intelligent sensing network. Due to the nature of wavelets, the technique is beneficial not only in reducing white noise but also in the mitigation of a wide range of interferences which are present in different application scenarios of CONASENSE. Another important issue in sensing area, in general, and in the wireless sensor networks, in particular, is the self-configuration and self-organization feature of these networks, or, in other words, the cognitive aspect of smart WSN. Intelligent CONASENSE sensors are aimed to transform the already existing network into an advanced, cognitive and decentralized infrastructure. The cognitive characteristic will be a viable choice for future WSN. In this context the cognitive radio communication technique is strongly needed for the implementation of smart WSN on the physical system level dealing with information and communication technologies (ICT) hardware and technical interoperability. The ICT ideas of cognition and intelligence are required to make WSN smart, and to ensure their stability, reliability, and security. The cooperative and self-organization aspect of CONASENSE is the salient aspect of WSN of future that has to be deeply researched. Another important research area in the smart sensing is its greenness. As the smart WSN of the future will be sustainable no need to say that the automation process and the sensors communication and control in these intelligent networks should be green as well. Therefore, there will be an emergent need for developing energy efficient and green sensor technologies that optimize power consumption even while guaranteeing a desirable quality of service and a robust and secure communication/control performance. Green ICT technologies will certainly be on the agenda for future research and development of CONASENSE systems and networks. Copyright © 2014. River Publishers. All rights reserved.
- 31. 1.3 Architecture 15 Currently compressed sensing is a rapidly emerging field of research. Establishment of WSN in the light of mathematical theory of compressed sensingisthestate-of-theart.Duetosparsityofthesensedsignals,properbases are used for compressed sensing while satisfying the criteria for compressed sensing. The promising achievements in this area are the reduction of number of sensing elements and measurements, the reduction of the complexity of the sensing method, optimized use of sensing power, and the optimized number of sensing nodes [43]. 1.3.3 e-Health In view of rising costs in healthcare, increasing percentage of ageing pop- ulation and the fact that many patients needing health-monitoring do not necessarily require hospitalisation, one needs to look for new approaches for the provision of low-cost (preventive) health services, especially for disabled, elderly and chronically ill patients [44–45]. On the other hand, the progress in ICT, biotechnologies and nanotechnologies accelerate innovations in the field, and lead to miniaturization and large-scale production of efficient and affordable products. Standardization that will ensure interoperability between devices and information systems will open up the way for large-scale and cost-effective deployment of e-health systems [46]. The CONASENSE may therefore play a major role in the provision of e-health services, hence for the QoL improvement. Thanks to recent advances in sensor technology and networks, the human health can be monitored by collecting data on specific physiological indicators (e.g. blood glucose level, blood pressure, electrocardiogram and electroen- cephalogram, portable magnetic resonance images, implantable hearing aid etc.), via in-, on-, and/or out-body sensors. An electronic system is reported in [47] that achieve thicknesses, effective elastic moduli, bending stiffnesses, and areal mass densities matched to the epidermis. Unlike traditional wafer- based technologies, laminating such devices onto the skin leads to conformal contact and adequate adhesion based on van der Waals interactions alone, in a manner that is mechanically invisible to the user. The system incorporates electrophysiological, temperature, and strain sensors, as well as transistors, light-emitting diodes, photodetectors, radio frequency inductors, capacitors, oscillators, and rectifying diodes. Solar cells and wireless coils provide options for power supply. This technology is designed and manufactured to measure electrical activity produced by the heart, brain, and skeletal muscles. Copyright © 2014. River Publishers. All rights reserved.
- 32. 16 Vision on CONASENSE Architecture Such systems typically perform sensing, data collection with user pro- file information, including data aggregation, data visualization, and analy- sis/alerting functions for the health professionals. The data, which is usually collected at a hub, is periodically transmitted to a server through a gateway (using IP). The database in the server may be used for preventative health care, physiological/functional monitoring, chronic disease management, and assessment of the QoL, e.g., fitness, diet or nutrition monitoring applications. In view of the multiplicity and mobility of sensors and users, association of the health monitoring data with patients requires serious consideration [48]. In e-health systems, the patients or sensing systems may update their data in real time through Internet. Hence, the record of a patient becomes available to authorized professionals anytime anywhere, for real-time monitoring and intervention in emergency. Such systems also provide new forms of interaction and coordination between health professionals and lead to novel scientific approaches for medical applications. E-health systems provide mobility to the patients via mobile health- monitoring devices [49]. Patient mobility also calls for wearable, outdoor and home-based applications. Physical and health conditions of patients can be monitored in real-time using sensors observing the environment and those that measure physiological parameters of the patient at home and hospital environments. Similar approaches may be followed for the safety of workers. Indoor positioning and tracking systems may be used in hospitals, for example to track expensive equipment, and to guide patients and health professionals inside the hospitals for more efficient and timely services. The health data can be stored on the sensor nodes and analyzed offline, while emergency situations and reports may be made available to health workers through a remote database. Hence, stored data from multiple patients may be utilized for geographic and demographic analyses [50]. Mobility solutions for wireless body area networks (BANs) for healthcare are already available, through communications over low-power Personal Area Networks (6LoWPANs) using Internet protocol Ipv6 [51]. These systems can provide preventive healthcare, enhanced patient–doctor interaction and information exchange. Continuous health-monitoring allows immediate intervention in case of an emergency. Positioning, tracking and monitoring patients with asthma, diabetics, heart disease, Alzheimer disease, obesity [52] as well as visually impaired people, ambulance systems, small children, robotic wheelchairs, pregnancy, blood pressure, artificial arms/legs, drug addiction are believed to be important issues. Copyright © 2014. River Publishers. All rights reserved.
- 33. 1.3 Architecture 17 Modelling the physical channel in body-area networks (BANs) is the topic of intense research efforts [53]. Optimal use of relay nodes, adaptive approaches for managing outages and retransmissions, cross-layer optimiza- tion to share information between physical and media-access control (MAC) layers will definitely improve the overall system performance. The MAC- layer operation in BANs for e-health is addressed in the IEEE 802.15.6 draft standard for BAN [54]. For example, intra-body communication for continuous-monitoringofpatientswithartificialheartembodiesseriousissues, e.g., the operation of an antenna and the propagation of electromagnetic waves in human body, which is a nonhomogeneous lossy medium. Similarly, reliable signal transmission between sensors on the body under shadowing is still among the areas of interest. Positioning with high precision in the human body, which is strongly desired for surgical operations, is believed to be possible in the near/mid-term. The physiological data collected in e-health systems is bidirectional and distributed through Internet and/or in heterogeneous networks to all interested parties. The CONASENSE architecture should address the problems related to protocol design, accuracy, reliability, data security, protection, privacy of diagnoses, range, operation time, and interoperability between medical devices [55–57]. These studies should be supported by databases, intelligent decision support algorithms and programming languages. Recent efforts on medical device interoperability resulted in a standard ISO/IEEE 11073 PHD [58] for communications between health devices such as USB, Bluetooth, and ZigBee. CONASENSE architecture should also provide intelligent solutions for wireless e-health applications including healthcare telemetry and tele- medicine. Even the patients at some remote locations and/or unable to reach a nearby health center may be monitored and managed; remote diagnosis and emergency intervention can be accomplished by tele-medicine. Improved and low-cost healthcare services may be provided to poor and geographically remote patients by exploiting new technologies. In that context, such services may provide a low-cost healthcare solution in less developed geographic regions in the world. Terrestrial and satellite segments of the CONASENSE architecture pro- vide the deployment of interconnected integrated and interoperable telecom- munications network for e-health applications. e-Health services are provided by an Interactive Service Platform, including real-time audio and video interactions among patients, specialists and health service providers. Both citizens and physicians can access the interactive Service Platform from Copyright © 2014. River Publishers. All rights reserved.
- 34. 18 Vision on CONASENSE Architecture different locations (e.g. Health Points, Hospitals, Home) regardless of the chosen access technology, either satellite or terrestrial. The Service Platform will share health information among different applications and services (Self- Care and Assisted). It is based on the Health Integration Engine (HIE): this middleware guarantees the information exchange between the e-Health subsystems Personal Health Media (PHM), Electronic Health Record (EHR), Electronic Clinical Research Form (ECRF), Clinical Health record (CHR) and the user access points. 1.3.4 Security and Emergency Services Professional mobile radio (PMR) systems, e.g., APCO and TETRA, are employed by police, fire departments, ambulance systems etc. for security and emergency applications. Compared with ubiquitous commercial mobile radio systems, these systems have some additional requirements for survivability in disaster scenarios, operation in relay mode without needing base stations, larger coverage areas (higher transmit powers) etc. Interoperability between mobile radio and PMR systems is strongly desired. 4G systems may also provide services to the PMR users via virtual private networks. Features like relaying and survivability may be provided through diversity and coordination between base stations. Incorporation of sensing capability and accurate time- and positioning estimation in mobile radio systems may put them in a very strong position for monitoring, and management of disaster, emergency, mine-accidents, earthquake, fire-fighting, police patrolling, and intruder/fraud detection. Rapid and accurate position estimation/navigation is very often needed in military applications. With accurate position estimation, a variety of applications and services, suchaslocationsensitivebilling,andimprovedtrafficmanagementforcellular networks may become feasible. Positioning of a mobile terminal is considered to be critical for position-aware services such as such as E-911 in USA and E-112 in European Union (EU) for emergency calls [59], [60]. Noting that mobile-originated emergency calls are continually increasing and about 50% of all emergency calls in the EU are originated by mobile users, location estimation of a mobile user making an emergency call is strongly desired. 1.3.5 Traffic Management and Control CONASENSE may also have a significant contribution in the domain of traffic management and control. For example, monitoring and management of highway/tunnel/bridge traffic which may need to be diverted, under Copyright © 2014. River Publishers. All rights reserved.
- 35. 1.3 Architecture 19 congestion, to alternative itineraries may save valuable money and time and reduce pollution. Intelligent transport systems (ITS) will significantly alle- viate the urban traffic via inter-vehicular communications, communications between the terminals along the roads, and broadcasting to vehicles the last- minute traffic information. Controlling the distance between vehicles on the road by onboard radars under rain/snow/fog is strongly desired [61–66]. Sim- ilarly monitoring and navigation of the traffic in railways, harbors/ports/seas, e.g., yachts, ships etc., air traffic (air traffic control and taxi) and UAV’s are among the application areas of the CONASENSE. Monitoring and controlling the border traffic between countries may also be used to prevent illegal border crossings. Traffic control in shopping malls, banks, concert halls etc. may be desirable for statistical purposes as well as for security reasons. Concepts for traffic control, e.g., monitoring the migration paths, times and the density of wild animals, could be valuable for the protection of wild life. Similar arguments may be repeated for the monitoring of the farm animals. In summary, CONASENSE architecture should provide intelligent and flexible solutions in the area of traffic management and control. 1.3.6 Environment Monitoring and Protection Rapid growth of the world population, high cost of transforming already established and highly polluting manufacturing plants to become more environment-friendly constitutes serious threats to our planet. Fortunately, recent advances in CONASENSE-related technologies enable us to follow more environment-friendly approaches at lower costs. Higher resolutions in positioning and remote sensing is promising for monitoring and assessment of earth resources, agricultural harvest, forests, seas, wild life, water resources, weather/climate, ozone layer, electromagnetic and chemical pollution. The CONASENSE architecture should address this problem, which is believed to be increasing importance in mid- to far-terms, by integration of air-borne and ground-based positioning and remote sensing platforms operating in various frequency bands. 1.3.7 Smart Power Grid Smart power grid modernizes the current electricity delivery system by integrating ICT into generation, delivery, control and consumption of elec- trical energy for enhanced robustness against failures, efficiency, flexi- bility, adaptability, reliability and cost-effectiveness. In that sense, smart grid embodies a fusion of different technologies where electrical power Copyright © 2014. River Publishers. All rights reserved.
- 36. 20 Vision on CONASENSE Architecture engineering meets sensing, ICT, positioning, control etc. [67]. The com- munication protocols to be deployed for this purpose should modernize and optimize the operation of the power grid and provide an accessible and secure connection to all network users, especially for efficient use of distributed energy sources [68]. Through communications between intercon- nectedsensornodes,thesmartgridcontrolsequipmentandenergydistribution, isolates and restores power outages, facilitates the integration of renewable energy sources into the grid and allows users to optimize their energy consumption. Design of end-to-end QoS resource control architectures [69] and general cyber-physical systems [61], efficient schemes for admission control, monitor- ing/control of the smart grid and the fluctuations of the power load is believed to be of prime importance for smart power grid networks [70]. Reliability and security of integrated communication network of the Smart Grid should be guaranteed in very adverse power line channels, which suffer high attenuation, multipath, impulse noise, harmonics and distortion [71], and smart attacks [72]. In addition to more reliable power line channel models [60], robust modulation, coding, encryption [67], [72] and transmission techniques and computational models are needed for optimized physical layer performance. 1.4 Conclusions Emergence of enabling technologies and rapidly increasing demands for services related to communications, sensing and navigation provides a good opportunity for the integration of existing CONASENSE-related systems and to design a novel flexible architecture so as to meet present and future requirements. To achieve this goal, it is critical to identify the require- ments for energy, terminal/platform and receiver/system design concerning diverse application areas including e-health, security/emergency services, traffic management and control, environmental monitoring and protection, and smart power grid. Minimization of energy consumption and energy harvesting deserve special attention in the novel CONASENSE architecture design mainly because of requirements for mobility, high-data rate com- munications and signal processing and green communications. The novel CONASENSE architecture design should address problems and drawbacks of the existing infrastructures/architectures and be sufficiently flexible for future/potential developments. Consequently, the design of the CONASENSE architecture should be carried out so as not only to integrate existing and novel communications, navigation and sensing services but also to provide Copyright © 2014. River Publishers. All rights reserved.
- 37. References 21 smooth transition between existing and new systems in hardware and software. Acknowledgment The authors would like to thank the CONASENSE WG2 Members Ernestina Cianca, University of Rome, Prof. Ramjee Prasad, Aalborg University, Prof. Enrico Del Re, University of Firenze, Prof. Vladimir Poulkov, University of Sofia, Prof. K.C. Chen, National Taiwan University, Dr. Nicola Laurenti, University of Padua, and Dr. Silvester Heijnen, Christian Huygens Laboratories, for the fruitful discussions and their presentations during the WG2 meetings which inspired the authors. References [1] www.conasense.org [2] M. Safak, Potential Applications and Research Opportunities in the CONASENSE Initiative, Chapter 5 in CONASENSE Communications, Navigation, Sensing and Services, River Publishers, Alborg, 2013. [3] S.Y. Lien, S.-M. Cheng, S.-Y. Shih and K.-C. Chen, “Radio Resource Management for QoS Guarantees in Cyber-Physical Systems,” Special Issue on Cyber-Physical Systems, IEEE Transactions on Parallel and Distributed Systems, vol. 23, no. 9, pp. 1752–1761, September 2012. [4] P.Y. Chen, S.M. Cheng, K.C. Chen, “Smart Attacks in Smart Grid Communication Networks”, IEEE Communications Magazine, vol. 50, no. 8, pp. 24–29, August 2012. [5] K.C. Chen, S.Y. Lien, “Machine-to-machine communications:Technolo- gies and challenges”, to appear in the Ad Hoc Networks, 2013. [6] Bagheri, R., et al., “Software-Defined Radio Receiver: Dream to Real- ity,” IEEE Communications Magazine, Vol. 44, No. 8, August 2006, pp.111–118. [7] Valls, J., T. Sansaloni, A. Pérez-Pascual, V. Torres and V. Almenar, “The Use of CORDIC in Software Defined Radios: A Tutorial,” IEEE Communications Magazine, Vol.44, No. 9, September 2006, pp.46–50. [8] Minde, G. J., et al., “An Agile Radio for Wireless Innovation,” IEEE Communications Magazine, Vol.45, No.5, May 2007, pp.113–121. [9] Björkqvist, J., and S. Virtanen, “Convergence of Hardware and Software in Platforms for Radio Technologies,” IEEE Communications Magazine, Vol. 44, No. 11, November 2006, pp.52–57. Copyright © 2014. River Publishers. All rights reserved.
- 38. 22 Vision on CONASENSE Architecture [10] Alluri, V. B., J. R. Heath, and M. Lhamon, “A New Multichannel, Coherent Amplitude Modulated, Time-Division Multiplexed, Software- Defined Radio Receiver Architecture, and Field-Programmable-Gate- Array Technology Implementation,” IEEE Trans. Signal Processing, Vol. 58, No. 10, 2010, pp. 5369–5384. [11] GianniniV.,etal.,“A2-mm0.1–5GHzSoftware-DefinedRadioReceiver in 45-nm Digital CMOS,” IEEE Journal of Solid-State Circuits, Vol. 44, No. 12, December 2009, pp. 3486 – 3498. [12] M. Lucente et al., PLATON: Satellite remote sensing and telecommuni- cation by using millimeter waves, 2012 IEEE ESTEL Conference. [13] Haskins, C. B., and W. P. Millard, “Multi-band Software Defined Radio for Space-born Communications, Navigation, Radio Science, and Sensors,” IEEE Aerospace Conf., 2010, pp.1–9. [14] M.Safak, Wireless Sensor and Communication Nodes with Energy Har- vesting, CONASENSE Journal, vol. 1, pp.47–66, January 2014, doi: 10.13052/jconasense2246–2120.113. [15] Niyato, D., E. Hossain, M.M. Rashid and V. K. Bhargava, “Wireless sensor networks with energy harvesting technologies: a game-theoretic approach to optimal energy management,” IEEE Wireless Communica- tions, August 2007, pp. 90–96. [16] Nakajima, N., Short-range wireless network and wearable bio-sensors for healthcare applications, 2nd Int. Symposium on Applied Sciences in Biomedical and Communication Technologies (ISABEL 2009), 2009, pp.1–6 [17] Sudevalayam, S., and P. Kulkarni, “Energy Harvesting Sensor Nodes: Surveys and Implications,” IEEE Communications Surveys Tutorials, vol.13, no.3, 3rd Quarter 2011. [18] V. Sharma, U. Mukherji, V. Joseph and S. Gupta, “Optimal energy management policies for energy harvesting sensor nodes,” IEEE Trans. Wireless Communications, vol. 9, no.4, pp.1326–1336, April 2010. [19] Joseph, V., V. Sharma, and U. Mukherji, “Optimal sleep-wake policies for an energy harvesting sensor node,” IEEE ICC, 2009. [20] R. Amirtharajah, J. Collier, J. Siebert, B. Zhou, and A. Chandrakasan, “DSPs for energy harvesting sensors, Applications and Architectures,” IEEE Pervasive Computing, July-Sept. 2005, pp. 72–79. [21] Tacca, M., P. Monti and A. Fumagalli, “Cooperative and reliable ARQ protocols for energy harvesting wireless sensor nodes,” IEEE Trans. Wireless Communications, vol.6, no.7, pp. 2519–2529, July 2007. Copyright © 2014. River Publishers. All rights reserved.
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- 42. 26 Vision on CONASENSE Architecture [59] Federal Communications Commission (FCC) Fact Sheet, “FCC Wireless 911 Requirements”, 2001. [60] EU Institutions Press Release, ”Commission Pushes for Rapid Deploy- ment of Location Enhanced 112 Emergency Services,” DN:IP/03/1122, Brussels, Belgium, July 2003. [61] Hartenstein, H., and K. P. Laberteaux, “A Tutorial Survey on Vehicular Ad Hoc Networks,” IEEE Communications Magazine, Vol. 46, No. 6, June 2008, pp. 164–171. [62] Karagiannis, G., et al., “Vehicular Networking: A Survey and Tutorial on Requirements, Architectures, Challenges, Standards and Solutions,” IEEE Communications Surveys Tutorials, Vol. 13, No. 4, Fourth Quarter 2011, pp.584–616. [63] Sichitiu, M. L., and M. Kihl, “Inter-Vehicle Communication Systems: A Survey,” IEEE Communications Surveys Tutorials, Vol. 10, No. 2, 2nd Quarter 2008, pp. 88–105. [64] Suthaputchakun, C., and Z. Sun, “Routing Protocol in Intervehicle Communication Systems: A Survey,” IEEE Communications Magazine, Vol.49, No.12, December 2011, pp. 150–156. [65] Acosta-Marum, G., and M. A. Ingram, “Six Time- and Frequency- Selective Empirical Channel Models for Vehicular Wireless LANs,” IEEEVehicularTechnology Magazine,Vol. 2, No. 4, Dec. 2007, pp.4–11. [66] Molisch, A. F., F. Tufvesson, J. Karedal, and C.F. Mecklenbrauker, “A Survey on Vehicle-to-Vehicle Propagation Channels,” IEEE Wireless Communications, vol.16, no.6, December 2009, pp.12–22 Fadlullah, Z. Md., et al., “Toward Secure Targeted Broadcast in Smart Grid,” IEEE Communications Magazine, Vol.50, No.5, May 2012, pp.150–156. [67] Fadlullah, Z. Md., et al., “Toward Secure Targeted Broadcast in Smart Grid,” IEEE Communications Magazine, Vol.50, No.5, May 2012, pp.150–156. [68] Lloret, J., P. Lorenz and A. Jamalipour, “Communication Protocols and Algorithms for the Smart Grid,” IEEE Communications Magazine, Vol.50, No.5, May 2012, pp.126–127. [69] Vallejo, A., A. Zaballos, J.M. Selga and J. Dalmau, “Next-generation QoS Control Architectures for Distributed Smart Grid Communication Networks,” IEEE Communications Magazine, Vol.50, No.5, May 2012, pp.128–134. [70] Zhou, L., J. J. P. C. Rodrigues and L. M. Oliveira, “QoE-driven Power Scheduling in Smart Grid: Architecture, Strategy, and Methodology,” IEEE Communications Magazine,Vol.50, No.5, May 2012, pp. 136–141. Copyright © 2014. River Publishers. All rights reserved.
- 43. Biographies 27 [71] Oksman, V., and J. Zhang, “G.HNEM: The New ITU-T Standard on Nar- rowband PLC Technology,” IEEE Communications Magazine, Vol.49, No.12, December 2011, pp.36–44. [72] Marmol, F. G., C. Sorge, O. Ugus, and G. M. Perez, “Do Not Snoop My habits: Preserving Privacy in the Smart grid,” IEEE Communications Magazine, Vol.50, No.5, May 2012, pp. 166–172. Biographies Mehmet Safak received the B.Sc. degree in Electrical Engineering from Middle East Tech- nical University, Ankara, Turkey in 1970 and M.Sc. and Ph.D. degrees from Louvain Univer- sity, Belgium in 1972 and 1975, respectively. He joined the Department of Electrical and Electronics Engineering of Hacettepe Uni- versity, Ankara, Turkey in 1975. He was a postdoctoralresearchfellowinEindhovenUni- versity of Technology, The Netherlands during the academic year 1975-1976. From 1984 to 1992, he was with the Satellite Communications Division of NATO C3 Agency (formerly SHAPE Technical Centre), The Hague, The Netherlands, as a principal scientist. During this period, he was involved with various aspects of military SATCOM systems andrepresentedNATOC3AgencyinvariousNATOcommitteesandmeetings. In 1993, he joined the Department of Electrical and Electronics Engineering of Eastern Mediterranean University, North Cyprus, as a full professor and was the Chairman from October 1994 to March 1996. Since March 1996, he is with the Department of Electrical and Electronics Engineering of Hacettepe University, Ankara, Turkey, where he acted as the Department Chairman during 1998-2001. He is currently the Head of the Telecommunications Group. He conducted and supervised projects, served as a consultant and orga- nized courses for various companies and institutions on diverse civilian and military communication systems. He served as a member of the executive committee of TUBITAK (Turkish Scientific and Technical Research Coun- cil)’s group on electrical and electronics engineering and informatics. He acted as reviewer in various national and EU projects and for distinguished Copyright © 2014. River Publishers. All rights reserved.
- 44. 28 Vision on CONASENSE Architecture journals. He was involved in the technical programme committee of many national and international conferences. He served as the Chair of 19th IEEE Conference on Signal Processing and Communications Applications (SIU 2011). He represented Turkey to COST Action 262 on Spread Spectrum Systems and Techniques in Wired and Wireless Communications. He acted as the chairman of the COST Action 289 Spectrum and Power Efficient Broadband Communications. He was involved with high frequency asymptotic techniques, reflector antennas, wave propagation in disturbed SATCOM links, design and anal- ysis of military SATCOM systems and spread spectrum communications. His recent research interests include multi-carrier communications, channel modelling, cooperative communications, cognitive radio and MIMO systems. Homayoun Nikookar is an Associate Professor in the Microwave Sensing Signals and Systems Group of Faculty of Electrical Engineering, Mathe- matics and Computer Science at Delft University of Technology. He has received several paper awards at international conferences and symposiums and the ‘Supervisor of theYear Award’at Delft Univer- sity of Technology in 2010. He is the Secretary of the scientific society on Communication, Navi- gation, Sensing and Services (CONASENSE). He has published more than 130 refereed journal and conference papers, coauthored a textbook on ‘Introduction to Ultra Wideband for Wireless Communications’, Springer 2009, and has authored the book ‘Wavelet Radio’, Cambridge University Press, 2013. Prof. dr. ir. Leo P. Ligthart, Ceng, FIET, FIEEE was born in Rotterdam, the Nether- lands, on September 15, 1946. He received an Engineer’s degree (cum laude) and a Doctor of Technology degree from Delft University of Technology in 1969 and 1985, respectively. He is Fellow of IET and IEEE. He received Doctorates (honoris causa) at Moscow State Technical University of Civil Avi- ation in 1999, Tomsk State University of Control Systems and Radio Electronics in 2001 and the Copyright © 2014. River Publishers. All rights reserved.
- 45. Biographies 29 Military Technical Academy Bucharest in 2010. He is academician of the Russian Academy of Transport. In 1988 he was appointed as professor on Radar Positioning and Nav- igation and since 1992, he has held the chair of Microwave Transmission, Radar and Remote Sensing in the Department of Electrical Engineering, Mathematics and Computer Science, Delft University of Technology. In 1994, he founded the International Research Center for Telecommunications and Radar (IRCTR) and was the director of IRCTR until 2011. He received several awards from Veder, IET, IEEE, EuMA and others. He is emeritus professor at the Delft University of Technology, is guest professor at ITB, Bandung and Universitas Indonesia in Jakarta and scientific advisor of IRCTR-Indonesia. He is founder and chairman of Conasense. He is member in the Board of Governors IEEE-AESS (2013–2015). He is founding member of the EuMA, organized the first EuMW in 1998, the first EuRAD conference in 2004 and various conferences and symposia. He gave post-graduate courses on antennas, propagation and radio and radar applications. He was advisor in several scientific councils and consultant for companies. Prof. Ligthart’s principal areas of specialization include antennas and propagation, radar and remote sensing, but he has also been active in satel- lite, mobile and radio communications. He has published over 600 papers and 2 books. Copyright © 2014. River Publishers. All rights reserved.
- 47. 2 Performance Analysis of the Communication Architecture to Broadcast Integrity Support Message Ernestina Cianca 1, Bilal Muhammad 1, Mauro De Sanctis 1, Marina Ruggieri 1 and Ramjee Prasad 2 1CTIF Italy (University of Rome “Tor Vergata”) 2CTIF (Aalborg University, Denmark) 2.1 Introduction Navigation capability is nowadays considered to be an assumed infrastructure and the knowledge of position (or any function of it such as speed, acceleration and heading) is nowadays fundamental to provide intelligent services for many different reasons. First of all, the service itself could be location-based, meaning that the type of service to be provided and its configuration is dependent on the user position. Furthermore, the knowledge of the position could be an important element to optimize the design and performance of the other two key functions that need to be performed to provide intelligent services, which are sensing and communications [1]. For instance, the knowledge of the position of the sensors nodes is important to optimize the efficient dissemination of data through the sensor network (routing algorithms, or sleep/awake energy saving mechanisms). In other cases, the knowledge of the position of the mobile users could be used to optimize the communication protocols and the resource usage; in a context where different radio access networks are available, the knowledge of the position of the mobile terminals could be used to allocate the resources or even predict the allocation within a heterogeneous Radio Access Network (RAN) infrastructure. In the EU WHERE project for instance [2], Convergence of Communications, Navigation, Sensing and Services, 31–50. c 2014 River Publishers. All rights reserved. Copyright © 2014. River Publishers. All rights reserved.
- 48. 32 Performance Analysis of the Communication Architecture the objective was to combine wireless communications and navigation for the benefit of future mobile radio systems. Nevertheless, the interaction between communication and navigation in this chapter is considered from a different point of view: how a communication infrastructure can be used to aid or to improve the performance of GNSS posi- tioning systems? For instance, it is well known that a way to improve accuracy and reliability of GNSS is by broadcasting GNSS corrections generated from a network of ground stations (local, regional or global) to the user via various data links, mostly 3G networks or communication satellites (i.e. EGNOS). The Real Time Kinetic (RTK) or Precise Point Positioning (PPP) represents two examples of this approach. The choice of the communication links has an impact on the final performance of this augmented GNSS system. For instance, GEO satellites such as EGNOS, encounters limitations in urban and rural canyons, accentuated at high latitudes where the EGNOS GEO satellites are seen with low elevation angles. Studies have been done to assess the performance of EGNOS augmented GNSS for road applications [3]. Moreover, what is the impact on the communication network of the added load due to the need to transmit those corrections? This question could be important in future wide-area ITS services for urban users. Some studies have been carried out recently to reduce this load by using proper communication protocols and message format. Moreover, the performance assuming for instance less-frequent update of this broadcast information have been assessed in [4]. A communication infrastructure is needed also for broadcasting information for integrity support.This issue is gaining increasing attention and has not been deeply investigated yet. As it will be detailed in the next Sections, so far most of the works have focused on the integrity algorithm, assuming that the information contained in the so-called Integrity Support Message (ISM) is available within the required time. However, it is becoming increasingly important to better understand what is the impact of the communication architecture infrastructure that will have to disseminate these messages and what is the interaction between the format, content, frequency of update of this information, with and the requirements and capability of the chosen communication technologies. Some recent work has studied the design drivers for the Integrity Support Message architecture [5] [6]. The required size of ground monitoring networks, bounding methodology, and Time to ISM Alert are among the ISM architecture design drivers. Equally important is the dissemination network for the delivery of ISM to the final user. The choice of dissemination network strongly affects the underlying ISM architecture. In this Chapter we investigate the possibility to use TETRA Copyright © 2014. River Publishers. All rights reserved.
- 49. 2.2 Integrity for Aviation Users 33 standard developed by the European Telecommunication Standards Insti- tute (ETSI) [7] to disseminate ISM messages to Public Regulated Services (PRS) aviation users. TETRA could represent a more robust (to jamming and spoofing) and low cost communication technology for the distribution of ISM to PRS users. We present preliminary results of end-to-end delay to deliver short ISM latency message to the state aircraft using TETRA network. The Chapter is organized as follows: Section 2 presents the concept of integrity for aviation users, the requirements and existing integrity provi- sion architectures; Section 3 explains more in details the Advanced RAIM algorithm for the provision of vertical guidance and presents possible ISM contents, formats and dissemination networks; Galileo PRS services main characteristics are presented in Section 4; TETRA standard and our proposed ISM dissemination architecture are presented in Section 5 and 6; in Section 7 the performance in terms of latency of the proposed architecture are presented; final remarks are drawn in Section 8. 2.2 Integrity for Aviation Users Integrity is the measure of trust that can be placed in the correctness of the information provided by the navigation system. It includes the ability of the navigation system to provide timely alerts to navigation users when the system must not be used for the intended period of operation. The navigation system issues an alert within a given Time to Alert (TTA) when the error in the position solution exceeds a predefined Vertical Alert Limit (VAL) or Horizontal Alert Limit (HAL). In addition to integrity, other performance metrics of a navigation system are the accuracy, continuity and availability. The accuracy is the deviation of the estimated position solution from the true position solution. The continuity of a navigation system is its capability to perform its function without non-scheduled interruptions for the intended period of operation. The availability is defined, as the fraction of the time the navigation system is usable as compliance to accuracy, integrity, and continuity requirements for a given phase of flight. The Required Navi- gation Performance (RNP) for landing a civil aircraft [8] [9] is described in Table 2.1. The maximum probability of integrity failure or integrity risk defines the probabilitythatthenavigationsystemdoesnotissuealerttothenavigationuser within the given TTA given that the position solution exceeds the predefined VAL or HAL. On the other hand, continuity risk defines the unexpected loss Copyright © 2014. River Publishers. All rights reserved.
- 50. 34 Performance Analysis of the Communication Architecture Table 2.1 Required Navigation Performance for landing a civil aircraft Aircraft Accuracy Integrity Maximum Probabilities Phase of (2σ or 95%) Alert Limits (4-62σ) Time To Alert of Failure Flight Vertical Horizontal Vertical Horizontal Integrity Continuity NPA Initial Approach Departure N/A 0.22–0.74km N/A 1.85–3.7km 10 – 15s 10 −7 /hr 10 −4 /hr LNAV/VNAV 20m 220m 50m 556m 10s 1–2 x 10 −7 /150s 4.8 x 10 −6 /15s LPV 16m AVP-I 35m 40m APV-II 8m 20m 6s LPV-200 4m 35m Precision Approach CAT-I 10m Precision Approach CAT-II/III 2.9m 6.9m 5.3m 17m 2s 10 −9 /150s 4 x 10 −6 /15s Copyright © 2014. River Publishers. All rights reserved.
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