Spectrum Sharing Analysis of Cognitive System Through Enery Harvesting and Interference Negligence Technique

International Journal of Trend in Scientific Research and Development (IJTSRD)
Volume: 3 | Issue: 4 | May-Jun 2019 Available Online: www.ijtsrd.com e-ISSN: 2456 - 6470
@ IJTSRD | Unique Paper ID - IJTSRD23756 | Volume – 3 | Issue – 4 | May-Jun 2019 Page: 652
Spectrum Sharing Analysis of Cognitive System Through Enery
Harvesting and Interference Negligence Technique
Gurvinder Singh1, Rashmi Raj2
1M.Tech Scholar, 2Assistant Professor
1,2Department of Electronics and Communication Engineering,
Universal Institute of Engineering & Technology, Mohali, Punjab, India
How to cite this paper:GurvinderSingh
| Rashmi Raj "Spectrum Sharing
Analysis of Cognitive System Through
Enery Harvesting and Interference
Negligence Technique" Published in
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(ijtsrd), ISSN: 2456-
6470, Volume-3 |
Issue-4, June 2019,
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ABSTRACT
In this letter, a novel approach for solving the power and spectrum issues in
wireless sensor network (WSN) has been proposed.Typically,adeployedsensor
node is programmed to periodically send the data to the central base station
(CBS). Moreover, most of the sensornodesaredeployedinahostileenvironment
where replacing a power supply may not be feasible. In the proposed work, we
intend to solve the dual problem of spectrum and power for WSN by utilizing
techniques such as cooperativespectrumsharing(CSS) andRF (radiofrequency)
energy harvesting, respectively. Specifically, by characterizing the WSN as an
energy constrained secondary user, which will harvest power and spectrum
from the primary user, we have shown that significant performancegainscanbe
obtained for both primary and secondary users. Closed form expressions for
outage probability under a Nakagamifadingchannelhavebeenderived forboth
primary and secondary users. Furthermore, the theoretical results have been
compared with simulation results to validate the proposed analysis.
Keywords: Cooperative spectrum sharing, WSN, RF energy harvesting
INTRODUCTION
Recently there has been growingimpetuson developingsmartcitiesthoroughout
the world [1], [2]. Smart city is an intelligent city that is able to integrate and
synthesize data for many purposes which helps in improving the quality of life in
cities. The smart city is an innovation of Information and Com- munication
Technology (ICT), which is based upon Internet of thing (IoT), where the
motivation is to connect different parts of the city by using sensors which will be
useful in real-time monitoring of the public infrastructures
such as bridges, roads, buildings as wellasclimateconditions
[1]. Apart from above, the concept of “smartness” has also
been brought in technolo- gies such as smart meters, smart
grid, energy conservatism, recycling,waste managementetc.
[1]. In further boost to above technology, countries such as
India has recently approved a proposal to invest heavily in
smart city development [2]. For effective development of
smartcity,sensorshavetobedeployed in very large numbers
and they havetobeinterconnected, so that the collecteddata
can be transmittedtoaCBS,whereintelligentdecisionsbased
on this data can be made [1]. There are few issues identified
in the aforementioned definition i.e. deployment of sensors
throughout the city and transfer the collected information to
the CBS which require both power and frequency spectrum.
As the sensor nodes do not need to send the data all the time,
therefore providing a dedicated spectrum to WSN is not an
economically viable approach. Furthermore in case of WSN,
providing energy storage mechanism is a critical issue in
terms of space and location. In this paper, to alleviate the
above issues, we propose a self-sustaining wireless sensor
network that will utilize advance techniques such as
cooperative spectrum sharing (CSS) [3] and RF energy
harvesting (EH) to satisfy its requirement of spectrum and
power respectively. In CSS, an unlicensed (secondary/
cognitive) user is allowed to coexist in licensed spectrum of
primary user (PU) on the condition that secondary user (SU)
will assist the PU to achieve its target rate of communication
[3]. Moreover, instead of using an internalbatteryorexternal
recharging mechanism for its operation, it will prefer other
sources of renewable energy like thermal, solar, wind,
mechanical etc. The most reliable one, in case of WSN, is
harvesting energy from the RF signals present in the
environment,commonlyknownasRForwirelessEH.Various
studies have shown that the wirelessEHistheviablesolution
in solving the issues of energy constrained systems [4].
Hence in the proposed work, we characterize WSN as an
energy-constrained SU, which will harvest energy and
spectrum from PU, in return, it will ensure that PU meets its
target rate of communication.
Some recent work have incorporated RF EH in cooperative
relaying [5]–[7] where a single node operates for both EH
and information processing. In [5] tworelayingprotocolsare
discussed for Rayleigh fading channel, namely power
splittingbased relay (PSR) and time switching-based relay
(TSR). In PSR, relay utilizes fraction of signal power coming
from source for EH and remaining power for information
processing. In TSR, relaywill harvestenergyinEHperiodand
IJTSRD23756

International Journal of Trend in Scientific Research and Development (IJTSRD) @ www.ijtsrd.com eISSN: 2456-6470
remaining time is used for information processing. Here,
relay is used to amplify the source data andforward it tothe
destination. No spectrum sharing has been discussed. Both
[6], [7] have discussed spectrum sharing protocol with EH
but in underlay mode. Moreover, SU is not helping the PU in
achieving the target rate of communication. In underlay
mode, some power constraint on SU is superimposed so that
SU will cause only an acceptable amount of interference at
PU.
In this paper, a two phase protocol for energy as well as
spectrum harvesting alongwith information transmission in
overlay mode has been proposed for Nakagami fading
channel. In the proposed protocol, a sensor node which acts
as a decode- and-forward relay for the PUwillharvestenergy
from primary transmission and will use that harvested
energy to assist the PU in achieving the required rate of
communication by transmitting its data to the destination.
Moreover, part of the harvested energy will also be utilized
by the node to send its own data to CBS. However, as
compared to underlay mode of transmission, the proposed
overlayprotocol does notsufferfrompowerconstraintatthe
relay node [8].
Fig. 1. (a) System model and (b) proposed protocol
illustration for energy harvesting and information
transmission at ST.
SYSTEM MODEL WITH MATHEMATICAL ANALYSIS:
In this architecture, primary and secondary system consists
of transmitter receiver pair known as Primary Transmitter-
Primary Receiver (PT-PR) and Secondary Transmitter-
Secondary Receiver (ST-SR) respectively. For simplicity, we
assume that thelinkbetweenPT-PRfails,andprimaryuseris
not able to achieve its target rate of communication, Rp (due
to physical obstacles, poor channel conditions etc.), in such
case PT will require some cooperation from neighbouring
nodes to forward its data to PR with target rate of Rpt. ST
node (if it can) will assist PT by forwarding its data to PR and
simultaneously transfer its own data to SR. As ST is self-
sustaining sensor node, it will harvest the required energy
fromsignal it received from PT. Thereforethewholeprotocol
works as follow: In first phase, PT will broadcast PU's signal
(xp) which will be received by ST and SR only. After receiving
the signal, ST will utilize ϼ amount of signal power to harvest
energy and remaining for signal decoding. In second phase,
this harvested energy willbeusedtotransferbothprimaryas
well as secondarysignal (xs). ST will assign some(α)amount
of power to xpand remaining to xs, so that target rate at PRis
met. As SR has prior knowledge of xp from phase 1, so it can
cancel the interference received in phase 2 and will extract
only the required signal i.e. xs. The information signal
received at ST during the first phase is given
by . where, Pp is the transmission
power of PT. Here, ST works as a power splittingbased relay,
the power is split in the ratio of , is for energy
harvesting and for information processing,
Signal received by energy harvester is given by
. The harvested energy at ST
for half of the block time of length T can be given by
where, istheenergyconversion
efficiency. The power will be dispensed for remaining T/2
time and hence given by
The signal received by information receiver is given by
Where, is the sampled AWGN due to RF
band to baseband signal conversion. Therefore, total AWGN
noise at information receiver is
and .Consequently,the rateachieved
at information receiver of ST can be given by
=
Where, . In transmission phase 2, ST
decodes the received signal ( ) at informationreceiverand
transmits it along with by providing fraction of and
) power respectively. The signal received at PR is
givenby
where, is the AWGNreceivedatPRand .
After substituting , we get
.
The rate achieved at PR is given by
=
Where
OUTAGE PROBABILITY OF PRIMARY SYSTEM:
The outage probability for primary system can be given as
= 1- P
Above equation shows that outage at PR will be declared if
either ST or PR fails in decoding primary’s signal with target
rate of .
P =1- P =1-
Where , = , Γ(.,.) is the lower incomplete
gamma and Γ(.) gamma .
Where, z = . Above equation can be
rewritten as,

The second equality is because of thefactthatfor ,
the z term will be negative and the probability of gamma
distribution greater than a negative number is always 1.
Moreover for , ztend to + and the probability of
product of gamma distribution less than + is also 1. Now
solving for first equality when z is positive, using concept of
product of two RVs, we obtain
Using above equations we get,
Where, Using (4.35),(4.36) and (4.40) we get ,
Above Equation can be obtained in closed form
Where,G[.] is the Meijer G-function. For m=1 Nakagami
fading reduces to Rayleigh Fading Channel and reduces to
SIMULATION RESULTS AND DISCUSSION
In this section we have plotted outage probability for
primary and secondary system with respect to location of
the nodes in Fig. 2 and 3 respectively. We have considered
The path loss exponent (i.e. v) is
considered to be 3. The target rate for both systems are
considered to be 1 i.e. RP = RS = 1. The results are shownfor:
two different values of m i.e. m = 0.5 (half Gaussian
pulse), 1 (Rayleigh fading)
two different values of ρ i.e. ρ = 0.25, 0.75
two different values of η i.e. η = 0.5, 1
for α = 0.8
distance of d (where, 0.1 ≤ d ≤ 0.9) between PT-ST node
and (1-d) between ST-PR,
ST-SR links. PT-SR distance is assumed to be 1. It is very
obvious that with increasing value of m, fading will become
less severe; therefore outage probability decreases when m
changes from 0.5 to 1 in both Fig. 2 and 3
Fig. 2. Outage probability for primary system.
Fig. 3. Outage probability for Secondary system.
From Fig. 2 , it can be observed that when d is small, outage
probability decreases with increasing ρ, as less value of d
indicates PT and ST are closed enough and hence more
energy can be saved by using large ρ. However, when d≥ 0.8,
we need to choose small value of ρ in order to have less
outage probability. The reason for this is, as ST is moving
away from PT, it will require more power for decoding the
signal correctly. So proper choice of ρ depends on the
location of nodes. Similarly, Fig. 3 illustrates the outage
probability of secondary system with respect to d. Thetrend
observed in secondary system is quite similar to that of
primary system. This can be explained as follows. Since the
outage probability of secondary system isalsodependenton
the successful decoding of primary signal by ST in Phase 1,
hence as d (i.e.. distance between PT-ST) increases the
probability of successful decoding of primary signalreduces
hence the outage increases.Furthermore,when d≥ 0.8,more
power is required for decoding and less for transmission,
hence outage probability decreases for ρ = 0.25.
CONCLUSION
In this paper, we proposed a self-sustaining protocol for
WSN. In this protocol, WSN, which is characterized as a
secondary user can harvest both energy and spectrum from
primary signal transmission. In exchange for access to
primary signal spectrum, it will help the primary user in
achieving the target rate of communication. The excellent
agreement between simulated results and the analytically

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Spectrum Sharing Analysis of Cognitive System Through Enery Harvesting and Interference Negligence Technique

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