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123
SPRINGER BRIEFS IN
ELECTRICAL AND COMPUTER ENGINEERING
Nan Cheng
Xuemin (Sherman) Shen
Opportunistic
Spectrum
Utilization
inVehicular
Communication
Networks

SpringerBriefs in Electrical and Computer
Engineering
More information about this series at http://www.springer.com/series/10059

Opportunistic Spectrum Utilization in Vehicular Communication Networks 1st Edition Nan Cheng

Nan Cheng • Xuemin (Sherman) Shen
Opportunistic Spectrum
Utilization in Vehicular
Communication Networks
123

Nan Cheng
Department of Electrical
and Computer Engineering
University of Waterloo
Waterloo, ON, Canada
Department of Electrical
and Computer Engineering
University of Waterloo
Waterloo, ON, Canada
ISSN 2191-8112 ISSN 2191-8120 (electronic)
SpringerBriefs in Electrical and Computer Engineering
ISBN 978-3-319-20444-4 ISBN 978-3-319-20445-1 (eBook)
DOI 10.1007/978-3-319-20445-1
Library of Congress Control Number: 2015942246
Springer Cham Heidelberg New York Dordrecht London
© The Author(s) 2016
This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of
the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation,
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The use of general descriptive names, registered names, trademarks, service marks, etc. in this publication
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The publisher, the authors and the editors are safe to assume that the advice and information in this book
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Printed on acid-free paper
Springer International Publishing AG Switzerland is part of Springer Science+Business Media (www.
springer.com)

Preface
VehiculAr NETworks (VANETs) have been envisioned to improve road safety and
efficiency, and provide Internet access on the move, by incorporating wireless
communication and informatics technologies into the road transportation system.
VANETs can facilitate a myriad of attractive applications related to road safety (e.g.,
collision avoidance, safety warnings, and remote vehicle diagnostic), infotainment
(e.g., web browsing, file downloading, and video streaming), and traffic efficiency
improvement and traffic management (e.g., real-time traffic notification and elec-
tronic tickets). Through the evolving VANETs applications and services, not only
the road safety and efficiency can be greatly enhanced, but also the driving and
in-vehicle experiences can be improved.
In this monograph, we focus on the utilization of opportunistic spectrum bands,
including both unlicensed bands and licensed bands for VANETs, in order to
improve the performance of VANETs and facilitate more data-craving applications.
The research is of great importance since VANETs are facing spectrum scarcity
problem due to the dramatic growth of mobile data traffic and the limited bandwidth
of dedicated vehicular communication band. In Chap. 1, we overview VANETs and
describe the problem of spectrum scarcity. In Chap. 2, we provide a comprehensive
survey on existing opportunistic spectra utilization methods. In Chap. 3, we study
the utilization of licensed spectrum through cognitive radio. Specifically, the
probability distribution of the channel availability is first derived by means of a
finite-state continuous-time Markov chain (CTMC), jointly considering the mobility
of vehicles, and the spatial distribution and the temporal channel usage pattern of
primary transmitters. Using the channel availability statistics, we propose a game
theoretic spectrum access scheme for vehicles to opportunistically access licensed
channels in a distributed manner. In Chap. 4, we investigate on the data delivery
through WiFi access network in vehicular communication environment, focusing
on the analysis of delay and throughput performance. In specific, we consider
a generic vehicular user having Poisson data service arrival to download/upload
data from/to the Internet via sparsely deployed WiFi networks (want-to) or the
cellular network providing full service coverage (have-to). In this scenario, the
WiFi offloading performance, characterized by offloading effectiveness, is analyzed
v

vi Preface
under the requirement of a desired average service delay which is the time the data
services can be deferred for WiFi availability. We establish the theoretical relation
between offloading effectiveness and average service delay by an M/G/1/K queueing
model, and the tradeoff is examined. Finally, conclusions and future research
directions are given in Chap. 5. This monograph validates the feasibility of using
opportunistic spectra (cognitive radio and WiFi) for VANETs, and also evaluates the
performance of such opportunistic vehicular communication paradigms. Therefore,
this monograph can provide valuable insights on the design and deployment of
future VANETs.
We would like to thank Prof. Jon W. Mark, Dr. Ning Lu, Dr. Ning Zhang, Dr.
Tom H. Luan, from Broadband Communications Research (BBCR) Group at the
University of Waterloo, and Prof. Tingting Yang from Navigation College at Dalian
Maritime University, for their contributions in the presented research works. We also
would like to thank all the members of BBCR group for the valuable discussions and
their insightful suggestions, ideas, and comments. Special thanks are also due to the
staff at Springer ScienceCBusiness Media: Jennifer Malat and Melissa Fearon, for
their help throughout the publication preparation process.
Waterloo, ON, Canada Nan Cheng

Contents
1 Introduction ................................................................... 1
1.1 Overview of Vehicular Networks........................................ 1
1.2 Spectrum Scarcity in VANETs .......................................... 3
1.3 Aim of the Monograph................................................... 5
References ...................................................................... 6
2 Opportunistic Communication Spectra Utilization ...................... 9
2.1 Cognitive Radio (Licensed Bands) for VANETs ....................... 9
2.1.1 Spectrum Sensing in CR-VANETs ............................. 11
2.1.2 Dynamic Spectrum Access in CR-VANETs.................... 13
2.2 Opportunistic WiFi (Unlicensed Band) for VANETs .................. 14
2.2.1 Drive-thru Internet Access ...................................... 17
2.2.2 Vehicular WiFi Offloading ...................................... 20
2.3 Device-to-Device Communication ...................................... 23
2.3.1 Spectrum Efficiency ............................................. 23
2.3.2 Power Efficiency ................................................. 24
References ...................................................................... 25
3 Opportunistic Spectrum Access Through Cognitive Radio ............. 29
3.1 System Model ............................................................ 30
3.1.1 Urban Street Pattern ............................................. 30
3.1.2 Spatial Distribution of PTs ...................................... 31
3.1.3 Temporal Channel Usage Pattern of PTs ....................... 31
3.1.4 Mobility Model .................................................. 32
3.2 Channel Availability Analysis ........................................... 32
3.2.1 Analysis of Tin in Urban Scenarios ............................. 32
3.2.2 Analysis of Tout in Urban Scenarios ............................ 35
3.2.3 Estimation of in and out ....................................... 36
3.2.4 Derivation of Channel Availability.............................. 37
3.3 Game Theoretic Spectrum Access Scheme ............................. 39
3.3.1 Formulation of Spectrum Access Game ........................ 40
3.3.2 Nash Equilibrium in Channel Access Game ................... 41
vii

viii Contents
3.3.3 Uniform MAC ................................................... 42
3.3.4 Slotted ALOHA.................................................. 43
3.3.5 Efficiency Analysis .............................................. 43
3.3.6 Distributed Algorithms to Achieve NE with High ER ......... 45
3.4 Performance Evaluation ................................................. 46
3.5 Summary ................................................................. 50
Appendix ....................................................................... 51
References ...................................................................... 55
4 Performance Analysis of WiFi Offloading in Vehicular
Environments ................................................................. 57
4.1 System Model ............................................................ 59
4.1.1 Communication Model .......................................... 59
4.1.2 Mobility Model .................................................. 60
4.1.3 Queueing Model ................................................. 60
4.2 Derivation of Effective Service Time ................................... 61
4.3 Analysis of Queueing System and Offloading Performance ........... 63
4.3.1 Queue Analysis .................................................. 63
4.3.2 Offloading Performance ......................................... 65
4.4 Performance Evaluation ................................................. 66
4.5 Summary ................................................................. 68
References ...................................................................... 69
5 Conclusions and Future Directions ......................................... 71
5.1 Conclusions .............................................................. 71
5.2 Future Research Directions .............................................. 72
5.2.1 Exploiting D2D Communication for VANETs ................. 72
5.2.2 Opportunistic Communication Framework..................... 74
References ...................................................................... 75

Acronyms
AP Access Point
BS Base Station
CR Cognitive Radio
CRN Cognitive Radio Network
DSRC Dedicated Short Range Communications
D2D Device-to-device
EST Effective Service Time
GPS Global Positioning System
ITS Intelligent Transportation System
LTE Long Term Evolution
MAC Medium Access Control
MNO Mobile Network Operator
NE Nash Equilibrium
PDF Probability Density Function
PT Primary Transmitter
PU Primary User
QoS Quality of Service
RSU RoadSide Unit
SU Secondary User
VANETs VehiculAr NETworks
V2I Vehicle-to-infrastructure
V2V Vehicle-to-vehicle
VU Vehicular User
ix

Chapter 1
Introduction
Vehicular networks play a critical role in both developing the intelligent
transportation system and providing data services to vehicular users (VUs) by
incorporating wireless communication and informatics technologies into the
transportation system. However, due to the dramatic growth of mobile data traffic
and the limited bandwidth of dedicated vehicular communication band, vehicular
networks are facing spectrum scarcity problem in which spectrum resource is not
sufficient to satisfy the data requirements, and thus the performance is compromised.
In this chapter, we first overview the vehicular networks, and then describe the
spectrum scarcity problem in vehicular networks, including the causes, and the
impacts of the problem on the performance of vehicular networks. At last, the aim
of the monograph is provided.
1.1 Overview of Vehicular Networks
As an indispensable part of modern life, motor vehicles have continued to evolve
since people expect more than just vehicle quality and reliability. With the rapid
development of information and communication technologies, equipping automo-
biles with wireless communication capabilities is the frontier in the evolution to
the next generation intelligent transportation systems (ITS). In the last decade,
the emerging VehiculAr NETworks (VANETs) have attracted much interest from
both academia and industry, and significant progress has been made. VANETs are
envisioned to improve road safety and efficiency and provide Internet access on the
move, by incorporating wireless communication and informatics technologies into
the transportation system. VANETs can facilitate a myriad of attractive applications,
which are usually divided into two main categories: safety applications (e.g.,
collision avoidance, safety warnings, and remote vehicle diagnostic [1, 2]) and
N. Cheng, X. (Sherman) Shen, Opportunistic Spectrum Utilization in Vehicular
Communication Networks, SpringerBriefs in Electrical and Computer Engineering,
DOI 10.1007/978-3-319-20445-1_1
1

2 1 Introduction
infotainment applications (e.g., file downloading, web browsing, and audio/video
streaming [3, 4]). To support these various applications, the U.S. Federal Communi-
cation Commission (FCC) has allocated totally 75 MHz in the 5.9 GHz band for
Dedicated Short Range Communications (DSRC), based on the legacy of IEEE
802.11 standards (WiFi). On the other hand, the car manufacturers, suppliers and
research institutes in Europe have initialed the Car-to-Car Communication Consor-
tium (C2C-CC) with the main objective of utilizing inter-vehicle communication
to increase road safety and efficiency. IEEE has also developed IEEE 1609 family,
which consists of standards for wireless access in vehicular environments (WAVE).
Unlike most mobile ad hoc networks studied in the literature, VANETs present
unique characteristics, which impose distinguished challenges on networking.
(a) Potential large scale: VANETs are extremely large-scale mobile networks, which
can extend over the entire road network with a great amount of vehicles and roadside
units; (b) High mobility: the movement of vehicles make the environment in which
the VANET operators extremely dynamic. On highways, vehicle speed of over
150 km/h may occur, while in the city, the speed may exceed 60 km/h while the node
density may be very high, especially during rush hour; (c) Partitioned network: the
high mobility of vehicles may lead to large inter-vehicle distance in sparse scenarios,
and thus the network is usually partitioned, consisting of isolated clusters of nodes;
(d) Network topology and connectivity: the scenario of VANETs is very dynamic
because vehicles are constantly moving and changing their position. Therefore, the
network topology changes very often and the links between vehicles connect and
disconnect frequently. In addition, the links are also affected by the unstable outdoor
wireless channels; (e) Varied applications: applications of VANETs are of a large
variety and with different quality of service (QoS) requirements. All these features
dramatically complicate network protocol design, implementation and performance
evaluation.
VANETs basically consist of two types of communications, i.e., vehicle-to-
vehicle (V2V) communications and vehicle-to-infrastructure (V2I) communications
[5], as shown in Fig. 1.1. Installed with on-board units (OBUs), vehicles can
communicate with each other in ad hoc manner without the assistance of any
built infrastructure, which is referred to as V2V communications. By disseminating
information such as location, speed, and emergency warning messages to nearby
vehicles using V2V communications, VANETs can support varied applications such
as public safety applications, vehicular traffic coordination, road traffic management
[6], and some comfort applications (e.g., interactive gaming, and file sharing) [7, 8],
etc. In February 2014, the U.S. Department of Transportation announced that it
would begin to take steps to enable V2V communication technology for light
vehicles by early 2017. Communications between vehicles and communication
infrastructure (usually offers Internet access) are referred to as V2I communications.
Internet access has become an essential part of people’s daily life, and thus
is required anywhere and anytime. It is evidenced that the demand for high-
speed mobile Internet services has increased dramatically. A recent survey reveals
that Internet access is predicted to become a standard feature of future motor
vehicles [9]. Providing high-rate Internet access for vehicles can not only meet

1.2 Spectrum Scarcity in VANETs 3
Cellular BS
Footprint of cellular access
Parking
service
Cellular BS
CR BS
Wi-Fi AP
Wireless Access Infrastructure
Outband D2D
Cellular
WiFi
Wi-Fi AP
Inband D2D
Cognitive Radio
CR BS
Footprint of CR access
Footprint of WiFi access
Fig. 1.1 An overview of vehicular networks and available communication spectra
the ever-increasing Internet data demand of travelers, such as multi-media services,
but also enrich some safety-related applications, such as intelligent anti-theft and
tracking [10], online vehicle diagnosis [11], and so forth. Besides, jointly using
both V2V and V2I communications has attracted much attention since it can provide
better performance [12, 13].
Motivated by the vision and prospect of VANETs, both the academia, industry
and government institutions have done numerous activities. A review of past and
ongoing related programs and projects in USA, Japan and Europe can be found
in [1]. The standards of VANETs is reviewed in [6]. There are also a lot of research
works on VANETs, which have been surveyed in papers such as [1, 14].
1.2 Spectrum Scarcity in VANETs
The FCC has allocated 75 MHz spectrum to DSRC, and wireless wide area network
(WWAN) can be a practical and seamless way to provide Internet connectivity to
vehicles [15], such as off-the-shelf 3G and Long Term Evolution (LTE) cellular
networks. However, VANETs still face the problem of spectrum scarcity, which has
been demonstrated in [16]. The primary reasons of spectrum scarcity might be: (1)
the ever-increasing data intensive applications, such as high-quality video streaming
and user generated content (UGC), require a large amount of spectrum resources,
and thereby the quality of service (QoS) is difficult to satisfy merely by the dedicated
bandwidth; (2) the number of connected vehicles and devices is soaring, and thus

4 1 Introduction
the requirement for communication bandwidth increases dramatically. In urban
environments, the spectrum scarcity is more severe due to high vehicle density,
especially in some places where the vehicle density is much higher than normal
[8, 17].
Growth of demands: People tend to require richer contents when they are static
as well as on the road. The types of services required by people in the car have
turned from simple GPS, navigation, in-car phone and email to more various
services, featuring multimedia applications such as video/audio streaming, UGC
upload and sharing, online gaming, web surfing, etc. It is predicted that over two-
third of the global mobile data traffic will be video by 2018. These multimedia
applications often require large communication bandwidth, for example, the size of
a typical high definition movie is 5.93 GB while an Android game may need 1.8 GB
download/upload to play [18]. In addition, it is reported that the average speed of
mobile connection will surpass 2 Mbps by 2016, and the smartphones will generate
2.7 GB of data traffic on average per month.
Connected vehicles and devices: There are two types of entities in VANETs that
generate and consume data. The first type is connected vehicles that integrated with
Internet access capability and services. It is predicted that the percentage of Internet-
integrated vehicle services will jump from 10 % today to 90 % by 2020 [19]. The
connected vehicles can offer a number of integrated services to drivers (e.g., real-
time navigation, driver assistance, online diagnosis, etc.) as well as to passengers
(e.g., e-mails, video on demand, etc.). The other type of entities are the mobile
terminals of in-vehicle passengers. It is reported that the connected mobile devices
have become more than the world’s population by the end of 2013. Mobile users
expect to be connected anywhere and anytime, even when they are traveling in
vehicles.
Cellular communication technologies can provide reliable and ubiquitous Inter-
net access services and deliver data traffic for VANETs. Although 4G cellular
technologies such as LTE-A have extremely efficient physical and MAC layer
protocols, the cellular network nowadays is straining to meet the current mobile data
demand [20]; on the other hand, the explosive growth of mobile data traffic is no end
in sight, resulting in an increasingly severe overload problem. Consequently, simply
using cellular infrastructure for vehicle Internet access may worsen the overload
problem, and degrade the service performance of both non-vehicular and VUs. For
DSRC, comparing with the large mobile data demand, the bandwidth of DSRC is
limited. In urban environments, the spectrum scarcity is more severe due to high
vehicle density, especially in some places where the vehicle density is much higher
than normal [27, 28]. Moreover, due to the contention-based channel access model,
the performance of vehicular mobile data services cannot be guaranteed as in the
cellular-based technologies. In summary, the dedicated DSRC spectrum and the
cellular network may not be sufficient to provide a huge number of VUs with high-
quality services, and thus other solutions are required.

1.3 Aim of the Monograph 5
3
KHz
500
KHz
1
GHz
2
GHz
3
GHz
4
GHz
5
GHz
6
GHz
60
GHz
300
GHz
Broadcast TV
UHF Channels
Cell
phones
Cell
phones
Wi-Fi Wi-Fi DSRC
Ch172
5.850
5.860
5.870
5.880
5.890
5.900
5.910
5.920
Ch174 Ch176 Ch178 Ch180 Ch182 Ch184
Service Channels Service Channels
Frequency (GHz)
Control Channel
Critical Safety
of Life
High Power
Public Safety
Wi-Fi AP
Drive-Thru Internet
Licensed spectrum Unlicensed spectrum
Cognitive Radio
Device-to-Device
(D2D)
Fig. 1.2 Opportunistic spectrum bands for VANETs
1.3 Aim of the Monograph
As mentioned above, the dedicated 5.9 GHz band is not enough to satisfy the data
requirements of vehicular networks, while the cellular network is already congested
and may be very expensive to use. Other than DSRC and the cellular network, there
are several opportunistic spectrums that can be utilized for VANETs. The three main
opportunistic spectrums that can be utilized for VANETs are: (1) licensed spectrum
(e.g., TV white band) that can be utilized through cognitive radio technology, (2)
ISM spectrum that can be utilized by WiFi, and (3) cellular spectrum that can be
opportunistically utilized through device-to-device communications, as shown in
Fig. 1.1. The spectrum bands are shown in Fig. 1.2.
Cognitive radio (CR) is a possible complementary technology which allows
users to communicate opportunistically on spatially and/or temporally vacant
licensed radio spectrum for other communication systems. The IEEE 802.11af [21]
and the IEEE 802.22 [22] standards take advantage of dynamic spectrum access
(DSA) on TV white space to support wireless local area networks (WLANs) and
wireless regional area networks (WRANs), respectively.
With millions of hotspots deployed all over the world, WiFi, operating on
unlicensed spectrum is a complementary solution to deliver data content at low
cost. The feasibility of WiFi for outdoor Internet access at vehicular mobility has
been demonstrated in [23], referred to as drive-thru Internet. Recent advances in
Passpoint/Hotspot 2.0 powered by WiFi Alliance make WiFi more competitive
to provide secure connectivity and support seamless roaming. Different from the
cellular network, WiFi cannot provide fully coverage based on the deployment of
APs/hotspots, and thus the spectrum is spatially opportunistic for vehicles to use.
As a promising solution to offload the cellular network (CN), device-to-
device (D2D) communication technology has gained much attention recently [24].

6 1 Introduction
The basic tenet of D2D communications is that mobile users in proximity can
communicate directly with each other on the cellular spectrum (or other spectrum
bands) without traversing the base station or the backhaul networks. By utilizing
the proximity of mobile users and direct data transmission, D2D communications
can increase spectral efficiency and throughput, and reduce communication delay
for mobile users [25], which may be applied to many VANETs applications
such as video streaming, location-aware advertisement, safety related applications
and so forth. However, the spectrum for D2D communication is opportunistic in
the way that D2D communication should avoid interfering the uplink/downlink
cellular communication and the D2D communications of neighboring devices since
they may use the same spectrum resources. For example, it is shown in [26]
that the probability of having D2D links increases with the pathloss component
because the larger pathloss component implies weaker interference caused by
D2D transmissions to the cellular base station. The D2D communication is not
allowed when the required transmit power may cause interference to the cellular
uplink/downlink transmission higher than the minimal interference threshold.
CR, WiFi, and D2D communication have received extensive research attentions,
and have been proved to be capable of supporting broadband communication for
static or mobile users. However, the research works on utilizing such opportunistic
spectrum for VANETs are limited, considering the unique features of VANETs
aforementioned. A better understanding of how VANETs can effectively utilize the
spectrum opportunities will shed light not only to the design and implementation
of related protocols and mechanism, but also to economics issues, such as where
to deploy business WiFi hotspots and how to decide operator’s price strategy, etc.,
which motivates our work.
The aim of this monograph is to investigate how to utilize opportunistic spectra
for VANETs considering different scenarios and applications. Specifically, we try
to address the following research issues: (a) The features and characteristics of
spectrum opportunities for VANETs; and (b) how much data can be delivered by
exploiting the opportunistic spectrum. To answer these questions, in this mono-
graph, we analyze the spectrum availability jointly considering the characteristics
of the spectrum and the mobility of vehicles, and investigate the throughput and
delay performance of VANETs using the opportunistic spectra. Based on the
investigations on these issues, we can elaborate the insights and implications for
design and deployment of future VANETs.
References
1. Karagiannis G, Altintas O, Ekici E, Heijenk G, Jarupan B, Lin K, Weil T (2011) Vehicular
networking: a survey and tutorial on requirements, architectures, challenges, standards and
solutions. IEEE Commun Surv Tutorials 99:1–33
2. Omar H, Zhuang W, Li L (2013) VeMAC: a TDMA-based MAC protocol for reliable broadcast
in VANETs. IEEE Trans Mob Comput 12(9):1724–1736

References 7
3. Luan T, Cai L, Chen J, Shen X, Bai F (2014) Engineering a distributed infrastructure for
large-scale cost-effective content dissemination over urban vehicular networks. IEEE Trans
Veh Technol 63(3):1419–1435
4. Trullols-Cruces O, Fiore M, Barcelo-Ordinas J (2012) Cooperative download in vehicular
environments. IEEE Trans Mob Comput 11(4):663–678
5. Kenney J (2011) Dedicated short-range communications (DSRC) standards in the United
States. Proc IEEE 99(7):1162–1182
6. Moustafa H, Zhang Y (2009) Vehicular networks: techniques, standards, and applications.
Auerbach Publications, Boston
7. Bai F, Krishnamachari B (2010) Exploiting the wisdom of the crowd: localized, distributed
information-centric VANETs. IEEE Commun Mag 48(5):138–146
8. Lu R, Lin X, Luan T, Liang X, Shen X (2012) Pseudonym changing at social spots: an effective
strategy for location privacy in VANETs. IEEE Trans Veh Technol 61(1):86–96
9. KPMG’s global automotive executive survey (2012) [Online]. Available: http://www.
kpmg.com/GE/en/IssuesAndInsights/ArticlesPublications/Documents/Global-automotive-
executive-survey-2012.pdf
10. Ramadan M, Al-Khedher M, Al-Kheder S (2012) Intelligent anti-theft and tracking system for
automobiles. Int J Mach Learn Comput 2(1):88–92
11. Lin J, Chen S, Shih Y, Chen S (2009) A study on remote on-line diagnostic system for vehicles
by integrating the technology of OBD, GPS, and 3G. World Acad Sci Eng Technol 56:56
12. Cheng X, Yang L, Shen X, D2D for intelligent transportation systems: a feasibility study. IEEE
Trans Intell Transp Syst (to appear)
13. Zheng K, Liu F, Zheng Q, Xiang W, Wang W (2013) A graph-based cooperative scheduling
scheme for vehicular networks. IEEE Trans Veh Technol 62(4):1450–1458
14. Hartenstein H, Laberteaux K (2008) A tutorial survey on vehicular ad hoc networks. IEEE
Commun Mag 46(6):164–171
15. Chen B, Chan M (2009) Mobtorrent: a framework for mobile internet access from vehicles. In:
Proceedings of IEEE INFOCOM, Rio de Janeiro, April 2009
16. Ghandour AJ, Fawaz K, Artail H (2011) Data delivery guarantees in congested vehicular ad
hoc networks using cognitive networks. In: Proceedings of IEEE IWCMC, pp 871–876
17. Lu N, Luan T, Wang M, Shen X, Bai F (2012) Capacity and delay analysis for social-proximity
urban vehicular networks. In: Proceedings of IEEE INFOCOM, Orlando, March 2012
18. The 1000x mobile data challenge (2013) [Online]. Available: http://www.qualcomm.com/
media/documents/files/1000x-mobile-data-challenge.pdf
19. Connected Car Industry Report (2014) [Online]. Available: http://blog.digital.telefonica.com/
connected-car-report-2014/
20. Asadi A, Wang Q, Mancuso V (2014) A survey on device-to-device communication in cellular
networks. IEEE Commun Surv Tutorials 16(4):1801–1819
21. Flores AB, Guerra RE, Knightly EW, Ecclesine P, Pandey S (2013) IEEE 802.11 af: a standard
for TV white space spectrum sharing. IEEE Commun Mag 51(10):92–100
22. Stevenson CR, Chouinard G, Lei Z, Hu W, Shellhammer SJ, Caldwell W (2009) IEEE
802.22: the first cognitive radio wireless regional area network standard. IEEE Commun Mag
47(1):130–138
23. Bychkovsky V, Hull B, Miu A, Balakrishnan H, Madden S (2006) A measurement study of
vehicular internet access using in situ Wi-Fi networks. In: Proceedings of ACM MobiCom,
USA, September 2006
24. Doppler K, Rinne M, Wijting C, Ribeiro C, Hugl K (2009) Device-to-device communication
as an underlay to lte-advanced networks. IEEE Commun Mag 47(12):42–49
25. Golrezaei N, Molisch AF, Dimakis AG (2012) Base-station assisted Device-to-Device commu-
nications for high-throughput wireless video networks. In: Proceedings of IEEE ICC, Ottawa,
June 2012

8 1 Introduction
26. Johnson DB, Maltz DA (1996) Dynamic source routing in ad hoc wireless networks. In: Kluwer
international series in engineering and computer science. Springer, New York, pp 153–179
27. Cheng N, Zhang N, Lu N, Shen X, Mark J, Liu F (2014) Opportunistic Spectrum Access for
CR-VANETs: A Game-Theoretic Approach. IEEE Trans Veh Technol 63(1):237–251
28. Lu R, Lin X, Luan T, Liang X, Shen X (2012) Pseudonym changing at social spots: An effective
strategy for location privacy in VANETs. IEEE Trans Veh Technol 61(1):86–96

Chapter 2
Opportunistic Communication Spectra
Utilization
The objective of the monograph is to utilize the opportunistic spectra for VANETs
through technologies such as CR, WiFi, and D2D communications. This chapter
introduces the background and surveys the literature of these technologies, focusing
on research works related to VANETs.
2.1 Cognitive Radio (Licensed Bands) for VANETs
Cognitive radio is a promising approach to deal with the spectrum scarcity,
which enables unlicensed users to opportunistically exploit the spectrum owned
by licensed users [1, 2]. In cognitive radio networks (CRNs), licensed users and
unlicensed users are typically referred to as primary users (PUs) and secondary users
(SUs), respectively. Specifically, SUs perform spectrum sensing before transmis-
sion, through which they can identify and exploit spectrum opportunities without
interfering with the transmissions of PUs. By means of CR, not only can CRNs
provide better QoS for SUs, but also the spectrum utilization is significantly
improved. The main research topics of CRNs are spectrum sensing, spectrum
sharing, and spectrum decision (or spectrum access), which have been extensively
studied. The literature surveys for general CR networks and technologies can be
found in [3–5]. As an example of the application of CR technology, the under-
utilized TV white spaces (TVWS), which include VHF/UHF frequencies, have
been approved for non-TV communications in many countries such as USA and
Canada, using an emerging technology named Super WiFi. Several standards have
been established for Super WiFi, such as IEEE 802.22 and IEEE 802.11af [6].
A natural question then rises whether CR can be applied to solve the problem of
spectrum scarcity for VANETs. Recent researches in the literature demonstrate its
feasibility [7–10]. With CR technology, VANETs have been coined as CR-VANETs,
N. Cheng, X. (Sherman) Shen, Opportunistic Spectrum Utilization in Vehicular
Communication Networks, SpringerBriefs in Electrical and Computer Engineering,
DOI 10.1007/978-3-319-20445-1_2
9

10 2 Opportunistic Communication Spectra Utilization
Sensing-only Mode II
Local BS
Mode I
Mode II
Central BS
a b c
Fig. 2.1 Three deployment architecture of CR-VANETS with different device operations
whereby vehicles can opportunistically access licensed spectrum owned by other
systems, outside the IEEE 802.11p specified standard 5.9-GHz band, such as digital
television (DTV) and cellular networks. Considering the highly dynamic mobility,
vehicles are expected to exploit more spatial and temporal spectrum opportunities
along the road than stationary SUs. Other than simply placing a CR in vehicles,
CR-VANETs has many unique features that should be considered. Different from
static CR networks in which the spectrum availability is only affected by the
spectrum usage patterns of the primary network, in CR-VANETs, the spectrum
availability perceived by vehicles is also a function of the mobility of vehicles.
Therefore, spectrum sensing should be conducted over the movement path of
vehicles, leading to a spatiotemporal distribution, rather than temporal only. In
addition, the constrained nature of vehicle mobility according to street patterns
can be utilized. For example, the spectrum information in other locations can be
obtained by a vehicle through information exchange with vehicles moving from
those locations. And a vehicle can adapt its operations in advance using such
information and its predicted movement.
FCC defined various device operations of CR devices in [11], motivated by
spectrum database access capability, mobility and awareness of location. Different
operation modes are associated with different deployment architecture of CR-
VANETs, which are shown in Fig. 2.1.
• Spectrum database: Database which stores the usage information of TVWS. User
can query the spectrum database to check what frequencies can be used, for a
given location, without causing harmful interference to primary systems.
• Sensing-only mode: Devices cannot access spectrum database, and can access
the spectrum relying only on the spectrum sensing result, such as vehicles in
Fig. 2.1a. Cooperation can be used to improve the accuracy of spectrum sensing.
• Mode I: Devices with no geolocation and access capability to spectrum database.
However, they can query Mode II devices for spectrum information updates, such
as Mode I vehicles in Fig. 2.1b.
• Mode II: Devices are aware of location (e.g., via global positioning system (GPS)
device) and capable of accessing spectrum database, such as Mode II vehicles in
Fig. 2.1b, c.

2.1 Cognitive Radio (Licensed Bands) for VANETs 11
2.1.1 Spectrum Sensing in CR-VANETs
2.1.1.1 Per-Vehicle Sensing
In per-vehicle sensing, vehicles sense the channels using the traditional sensing
techniques, i.e., matched filter detection, energy detection, and cyclostationary fea-
ture detection [3]. Per-vehicle has the advantage that the implementation complexity
and network support is minimal since each vehicle senses the spectrum and makes
decision individually. However, the accuracy could be low given the high mobility
of vehicles and the obstructed environments that may cause shadowing and fading
effects. In [12], a mechanism is proposed to improve the accuracy of spectrum
sensing by exploring the signal correlation between TV and 2G cellular channels.
They prove that when the signals from adjacent TV and cellular transmitters are
received in a common place, a strong Received Signal Strength Indicator (RSSI)
can be detected. As a result, by comparing the signal with the fluctuations of cellular
channels, a sudden change in the TV band can be verified.
2.1.1.2 Geolocation-Based Sensing
As discussed above, FCC has recommended to use the location information and
spectrum database for CR users. The spectrum database can provide information
about the bands, such as the types, locations and specific protection requirements
of PUs, the availability of the bands, etc. Assisted by the spectrum database,
vehicles can adjust the transmission parameters to avoid interfering PUs without
sensing. Since most vehicles are equipped with localization systems (e.g., GPS),
geolocation-based sensing is suitable for vehicles. Some spectrum databases are
already available for users to access and query, for example, the TV query service
in the United States [13] and Google spectrum database (shown in Fig. 2.2). In [14],
spectrum database assisted CR-VANETs are proposed, in which fixed BSs are
deployed along the road and provide spectrum database access to nearby vehicles.
The deployment density of BSs is optimized to minimize the average cost of VUs
accessing spectrum database while guarantee a low level of error of estimating
available spectrum. The simulation results indicate that the cost of accessing
spectrum information increases with the density of BSs since more vehicles are
querying the spectrum database via BSs, which is a more expensive and accuracy
way than obtaining the spectrum database information from nearby vehicles or
spectrum sensing. In [15], a geo-location database approach is used to create
spectrum availability map on I-90 highway in the state of MA. Then, a discussion on
the number of non-contiguous blocks, the number of available channels, and design
of transceivers is followed.
However, several concerns about the spectrum database may include the cost of
building and maintaining the database, the coverage area of the service, significant
query overhead, etc. In [12], it is proposed to jointly use the spectrum database and

Fig. 2.2 TV white bands usage around Chicago from Google spectrum database. Colored
areas correspond to channels that are used (Color figure online) https://www.google.com/get/
spectrumdatabase/channel/
spectrum sensing. The signal correlation between TV and 2G cellular channels and
the mobility of vehicles are utilized to reduce the number of queries to spectrum
database in order to save the cost in terms of both money and communication
overhead. A vehicle can send the channel measurements to nearby vehicles,
containing the degree of correlation between TV and cellular channels. When
other vehicles arrive the same location, they can conduct spectrum sensing, and
make a decision on whether spectrum information update is necessary based on
measurements sent by former vehicles in this location. The results show that about
23 % queries are reduced, which can benefit spectrum database deployment.
2.1.1.3 Infrastructure-Based Sensing
A sensing coordination framework which utilizes road side units (RSUs) is proposed
in [16]. Unlike centralized sensing schemes in which a centralized controller gathers
sensing reports from all users and allocates the channels to users, in [16], multiple
RSUs are responsible to assist and coordinate the spectrum sensing and access for
nearby vehicles. RSUs continuously detect the occupancy of PUs at its location,
and then the coarse detection results are sent to vehicles. Vehicles conduct the fine-
grained sensing and access the channel correspondingly. The results indicate that
the sensing coordination framework outperforms the stand-alone sensing scheme in
terms of sensing overhead, successful sensing rate, probability of sensing conflict,
etc. One advantage of such schemes is that the change of government policies and

2.1 Cognitive Radio (Licensed Bands) for VANETs 13
PU parameters can be easily loaded in RSUs, which can further adapt the operation
and save the cost.
2.1.1.4 Cooperative Sensing Among Vehicles
A major concern about centralized sensing in CR-VANETs is discussed in [17].
Vehicles may have different views of spectrum occupancy, especially near the edge
of the range of primary systems, and thus it is difficult to set a BS or data fusion
center. Instead, in [17], a distributed collaborative sensing scheme is proposed.
Vehicles send the message about the belief on the existence of primary users to
neighboring vehicles, which is called belief propagation (BP). Upon receiving the
belief messages, vehicles combine the belief with their local observation to create
new belief messages. After several iterations, each vehicle is envisaged to have
a stable belief, and can conduct spectrum sensing accordingly. However, several
issues of this work could be further discussed, such as the convergence speed of the
iterations, the extent of belier propagation, etc.
Cooperative sensing between selected neighboring vehicles can be more efficient
than cooperation among all neighboring vehicles due to less message exchanges.
A light-weight cooperative sensing scheme can be seen in [18]. Roads are divided
into segments, and vehicles are allowed to gather spectrum information of h
segments ahead from vehicles in front, which is a priori spectrum availability
detection. Therefore, vehicles can decide the channel to use in advance so that
spectrum opportunities can be better utilized.
2.1.2 Dynamic Spectrum Access in CR-VANETs
The sensing results should be utilized to correctly choose the spectrum to access.
This can be done through different approaches, which can be categorized into PU
protection and QoS support, in terms of the target of the approaches.
2.1.2.1 Spectrum Access Approaches with PU Protection
In these approaches, vehicles access the spectrum with the goal of avoiding harmful
interference to licensed system and PUs. In [19], a learning structure is proposed
for channel selection in CR-VANETs. PU channel usage is modeled as “ON/OFF”
pattern, where in ON period, the channel usage follows “busy/idle” pattern, and in
OFF period, the PU does not transmit. The authors claimed that an instant spectrum
sensing is difficult to differentiate OFF periods from idle periods, while longer
sensing time reduces the utilization of OFF periods. Based on the fact that samples
of spectrum usage during the same time slot of days at the same location keep high
consistency, a channel selection is proposed jointly considering the past channel
selection experience and current channel conditions. Stored channel profiles are
used to select good channel candidates to sense and access, avoiding wasting limited

sensing time on other channels. In [20], some metrics for dynamic channel selection
are proposed and discussed. These metrics include: (1) channel data rate; (2) product
of channel utilization and data rate; (3) product of expected OFF period and data
rate.
2.1.2.2 Spectrum Access with QoS support
QoS support is important for VANETs, such as the delay constraint for safety
applications and bandwidth requirement of nonsafety applications. Therefore, QoS
support is a crucial consideration in dynamic spectrum access schemes. In [21], a
dynamic spectrum access scheme for vehicle-infrastructure uplink communication
is proposed to minimize the energy consumptions as well as guarantee the QoS. It
is claimed that energy efficient communication is important for VANETs to save
energy and reduce greenhouse gas emission, especially for the electric vehicles.
A joint optimization algorithm is proposed to minimize the energy consumption
while maintain the throughput requirement with the delay constraint of vehicular
communications. In [9], a dynamic channel selection scheme is proposed for
vehicle clusters, involving dynamic access to shared-use channels, reservation
of exclusive-used channels, and control of cluster size. Shared-use channel, i.e.,
licensed channels, can be accessed by vehicles in an opportunistic manner, while
exclusive-use channels are reserved for vehicle data transmission exclusively, such
as the DSRC spectrum band located at 5.9 GHz band. Channel selection is modeled
as an optimization problem under the constraints of QoS specifications and PU
protection, which is solved by constrained Markov decision process.
2.2 Opportunistic WiFi (Unlicensed Band) for VANETs
WiFi, as a popular wireless broadband access technology operating on the unli-
censed spectrum, provides the “last-hundred-meter” backhaul connection to private
or public Internet users. Through WiFi, data traffic that is originally targeted for
cellular networks can be delivered, which is referred to as WiFi offloading of
the mobile data. Hereafter, we use the term WiFi offloading to represent data
transmission through WiFi networks. The advantages of WiFi access can be found
in Table 2.1. These advantages make WiFi a cost-effective technology to offload
the cellular data traffic and alleviate the congestion of cellular networks. As a
matter of fact, WiFi is recognized as one of the primary cellular traffic offloading
technologies [24]. WiFi offloading has been extensively investigated for stationary
or slow moving users1
in [24–27]. It is shown that about 65 % of the cellular traffic
can be offloaded by merely switching the IP connection from the cellular network to
1
We refer to these users as non-vehicular users.

2.2 Opportunistic WiFi (Unlicensed Band) for VANETs 15
Table 2.1 The advantages of WiFi access
Advantage Description
Widely deployed infrastructure WiFi hotspots are widely deployed in many urban areas.
It is shown that WiFi access is available 53 % of the time
while walking around popular sites in some large cities [22].
Low cost WiFi access is often free of charge or inexpensive. For
example, KT Corporation in South Korea offers WiFi
services with $ 10 a month for unlimited data usage [23].
High availability of user devices Most of current mobile devices, such as smart phones,
tablets, and laptops are equipped with WiFi interfaces.
Efficient data transmission Currently WiFi technologies (IEEE 802.11 b/g) can provide
data rates of up to 54 Mbps. There are new technologies
under development or test, e.g., IEEE 802.11 ac/ad, which
can provide data transfer at several Gbps.
WiFi networks when WiFi connectivity is available (termed on-the-spot offloading).
Moreover, a large amount (above 80 %) of data can be offloaded by delaying the
data application [25] (termed delayed offloading), since the mobile users can wait
for WiFi connection and then transmit the data.
For moving vehicles, the feasibility of WiFi for outdoor Internet access at
vehicular speeds has been demonstrated in [28]. The built-in WiFi radio or
WiFi-enabled mobile devices on board can access the Internet when vehicles are
moving in the coverage of WiFi hotspots, which is referred to as the drive-thru
Internet access [29]. This access solution is workable to provide a cost-effective
data pipe for VUs [30], and with the increasing deployment of the urban-scale
WiFi networks (e.g., Google WiFi in the city of Mountain View) and carrier-
WiFi networks (i.e., WiFi networks deployed by cellular carriers), there will be
a rapid growth in vehicular Internet connectivity. WiFi offloading in vehicular
communication environments (or vehicular WiFi offloading) refers to delivering the
data to/from VUs through opportunistic WiFi networks, i.e., the drive-thru Internet.
Natural questions could arise here. How much data can be offloaded through
vehicular WiFi offloading? How to improve the offloading performance, i.e., to
offload more cellular traffic and guarantee the QoS of VUs simultaneously? Due to
high dynamics of vehicular communication environments, the effectiveness of WiFi
offloading for VUs should be carefully studied. The overview of vehicular WiFi
offloading is shown in Fig. 2.3. The Unique features and challenges of vehicular
WiFi offloading are elaborated from the following three aspects.
Drive-thru Internet access: In vehicular WiFi offloading, mobility plays a both
distinguishing and challenging role. During one drive-thru, i.e., the vehicle passing
the coverage area of one WiFi AP, the connection time is limited due to the small
coverage area of AP and the mobility of VUs, and therefore VUs can only obtain
a relatively small volume of data; VUs may experience multiple drive-thrus in a
short time period due to high mobility. This short and intermittent connectivity
can significantly impact offloading schemes, such as WiFi offloading potential

Internet
Router
Cellular Operator
WiFi Deployment
Control/Scheduling
Pricing/Incentive Model
Cellular BS
WiFi Hotspot
WiFi or Cellular?
WiFi prediction?
Defer Application?
Cost or performance?
Drive-Thru Internet #2
Drive-Thru Internet #1
Vehicle-Vehicle Link
Vehicle-Wifi Link
Vehicle-Cellular Link
Fig. 2.3 WiFi offloading in vehicular communication environments
prediction and network selection (cellular/WiFi). Fluctuating channels can lead to
high and bursty losses, resulting in disruptions to connectivity. Thus, proper handoff
schemes and transport protocols should be considered to reduce the disruptions and
adapt to the wireless losses.
Cellular operators: To ease congestion in cellular networks, cellular operators may
adopt certain commercial strategies to encourage data offloading, one of which is
stimulating VUs to transmit their data through opportunistic WiFi networks. Thus,
incentive models, such as variable service prices or reward mechanisms, should be
investigated. Moreover, cellular operators may deploy their own commercial or non-
commercial WiFi networks (carrier-WiFi networks) to offload mobile data, e.g., the
WiFi hotspots operated by ATT [31]. How to determine the WiFi deployment
strategy to attain optimal offloading performance is another research challenge.
Vehicular users: As the mobility pattern of vehicles can be partially predicted from
the mobility model, historic drive information, and driver preferences, the WiFi
offloading potential, i.e., data volume offloaded in the future, can be predicted in
a certain level. Based on the prediction and the knowledge of usage cost of cellular
and WiFi services, and the QoS requirements, it is possible for VUs to determine
when to use WiFi or cellular networks upon a service request emerging, in order to
get a good tradeoff between the cost and satisfaction level in terms of delay. It is
a challenging task to understand the cost-effectiveness of WiFi offloading from the
VUs’ perspective.
In this section, we focus on the problem of WiFi offloading in vehicular
environment. We discuss the challenges and identify the research issues related to
drive-thru Internet as well as vehicular WiFi offloading. Moreover, we review the
state-of-the-art solutions, providing rapid access to research results scattered over
many papers.

Table 2.2 Drive-thru Internet performance measurements—configuration
Scenario WiFi AP deployment Antenna
[29] Highway 802.11b Planned External/VU
[33] Highway 802.11g Planned 8 dBi/AP; 5 dBi/VU
[34] Traffic free road 802.11b Planned N/A
[35] Highway 802.11a/b/g Planned 7 dBi/AP
[28] Urban 802.11b Unplanned 5.5 dBi/VU
[32] Urban 802.11b/g Unplanned 3 dBi/VU
N/A: not applicable
2.2.1 Drive-thru Internet Access
The performance of drive-thru Internet is different from that of a normal WiFi net-
work which mostly serves non-vehicular users. The reasons are three-fold. Firstly,
high vehicle mobility results in a very short connection time to the WiFi AP, e.g.,
only several to tens of seconds, which greatly limits the volume of data transferred in
one connection time. Moreover, the time spent in WiFi association, authentication,
and IP configuration before data transfer can take up a considerable part of the
short connection time. Secondly, communications in vehicular environments suffer
from the high packet loss rate due to the channel fading and shadowing [32].
Thirdly, the stock WiFi protocol stack is not specifically designed for high mobility
environments.
Vehicular WiFi offloading mostly relies on the drive-thru Internet access oppor-
tunities, provided by open or planed WiFi networks. Therefore, we first review the
recent experimental and theoretical studies on drive-thru Internet. After that, we
discuss the vehicular WiFi offloading, including the challenges, research issues, and
existing and potential solutions.
We elaborate our discussion on drive-thru Internet from the following aspects.
2.2.1.1 Characteristics and Performance
To characterize and evaluate the performance of the drive-thru Internet access,
several real-world measurements have been conducted based on diverse test bed
experiments. The configurations and key results are summarized in Tables 2.2
and 2.3.
In [29, 33], the performance of the drive-thru Internet access is evaluated in
a planned scenario. Two APs are deployed closely along a highway, using IEEE
802.11b and 802.11g, respectively. The performances of User Datagram Protocol
(UDP) and Transmission Control Protocol (TCP) at different vehicle speeds (80,
120, and 180 km/h) and scenarios (AP to vehicle, vehicle to AP) are measured.
A very important feature of the drive-thru Internet observed from the experiment is
that VUs may encounter three phases successively during the drive-thru, i.e., entry,

Table 2.3 Drive-thru Internet performance measurements—results
Connection
establishment
time Connection time
Inter-connection
time Max rate
Data transfer in once
drive-thru
[29] Max 2.5 s 9 s @ 80 N/A TCP: 4.5 Mbps TCP: 6 MB @ 80
5 MB @ 120
1.5 MB @ 180
UDP: 5 Mbps UDP: 8.8 MB @ 80
7.8 MB @ 120
2.7 MB @ 180
[33] N/A N/A N/A 15 Mbps Max 110 MB
[34] 8 s 217 s @ 8 N/A TCP: 5.5 Mbps 92 MB @ 8
13.7 s @ 120 UDP: 3.5 Mbps 6.5 MB @ 120
[35] Mean 13.1 s 58 s N/A TCP: 27 Mbps Median 32 MB
[28] 366 ms 13 s Mean 75 s 30 KBps Median 216 KB
[32] 8 s N/A Median 32 s 86 Kbps; Median 32 MB
Mean 126 s
@ ˛: at ˛ (km/h); N/A: not applicable
production, and exit phases. In the entry and exit phases, due to the weak signal,
connection establishment delay, rate overestimation, etc, the data transmission
performance is not as good as that in the production phase. In [34], a similar test is
conducted on a traffic free road which means there is no interference or contention
among different VUs. It is shown that in such an environment, the performance
of the drive-thru Internet suffers most from the backhaul network or application
related issues rather than the wireless link problems. For example, with a 1 Mbps
bandwidth limitation of backhaul network, the TCP bulk data transferred within a
drive-thru reduces from 92 to 25 MB. In addition, a backhaul with 100 ms one-way
delay greatly degrades the performance of web services due to the time penalty of
HTTP requests and responses. The discussion on the problems that may cause the
performance degradation of the drive-thru Internet can be seen in [35].
In [28, 32], large-scale experimental evaluations with multiple vehicles in urban
scenarios have been conducted. Both of the data sets are collected from the city
of Boston with in situ open WiFi APs. TCP upload performance is investigated
in [28]. It is indicated that with fixed 1 Mbps MAC bit rate, the drive-thru Internet is
able to provide an (median) upload throughput of 30 KBps, and the median volume
of uploading data in once drive-thru is 216 KB. The average connection and inter-
connection (between successive connections) time are 13 s and 75 s, respectively.
This shows that although vehicles have short connection time with WiFi APs,
they may experience drive-thru access opportunities more frequently, compared
with low-mobility scenarios (median connection and inter-connection time 7.4 min
and 10.5 min, respectively [25]). In [32], the experiment shows a 86 kbps long-
term average data transfer rate averaged over both connection and inter-connection
periods. More importantly, two mechanisms to improve the performance are

proposed, namely Quick WiFi and CTP, to reduce the connection establishment time
and deal with the negative impact of packet loss on transportation layer protocols,
respectively.
2.2.1.2 Network Protocol
To improve the performance of the drive-thru Internet, in the literature, new
protocols or modification in existing protocols are developed. The efforts in the
literature include: (1) improving transport protocols to deal with the intermittent
connectivity and wireless losses [32]; (2) reducing connection establishment time
[32]; (3) enhancing MAC protocols for high mobility scenarios [36]; and (4) MAC
rate selection schemes [32, 35].
To deal with the bursty and high non-congestion wireless losses in vehicular
communication environments, a transport protocol called Cabernet transport proto-
col (CTP) is proposed in [32]. In CTP, a network-independent identifier is used by
both the host and the VU, allowing seamless migration among APs. Large send and
receive buffers can help to counter the outages (i.e., during the inter-connection
time). More importantly, CTP can distinguish wireless losses from congestion
losses, by periodically sending probe packets. Through an experimental evaluation,
CTP is demonstrated to achieve twice the throughput of TCP in the drive-thru
environment.
The connection time between a moving vehicle and a WiFi AP typically ranges
from seconds to tens of seconds in drive-thru scenarios, and not all of it can be used
for real data transfer. It takes some time to conduct AP association, authentication,
IP configuration, etc, before Internet connectivity is available. This time is called
connection establishment time. It is straightforward that the performance of data
transmission can be improved if this time duration can be reduced. In [32], a
mechanism named Quick WiFi is proposed to reduce the connection establishment
time and improve data transfer performance. The main idea of Quick WiFi is to
incorporate all processes related to connection establishment into one process, to
reduce the timeouts of related processes, and to make use of parallelism as much
as possible. It is shown that the connection establishment time can be reduced to
less than 400 ms. If the WiFi network is deployed and managed by one mobile
network operator (MNO), a simple yet effective method to reduce overhead due
to connection establishment is presented in [37], in which vehicles are allowed to
retain their IP address among different associations, and thus the authentication and
IP configuration are carried out only once.
The IEEE 802.11 Wireless Local Area Network (WLAN) MAC protocols are
designed for low-mobility scenarios, and consequently require modifications and
redesigns for the drive-thru Internet. In [36], the performance of IEEE 802.11
distributed coordination function (DCF) of the large-scale drive-thru Internet is
theoretically studied based on a Markov chain model. The impact of vehicle
mobility and network size (i.e., vehicle traffic density) on the MAC throughput
performance is also discussed. The key observation is that the normal operations

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