International Journal of Application or Innovation in Engineering & Management (IJAIEM)
Web Site: www.ijaiem.org Email: editor@ijaiem.org, editorijaiem@gmail.com
Volume 2, Issue 6, June 2013
ISSN 2319 - 4847
Throughput Analysis of Spectrum in Cognitive
Radio Ad Hoc Network
Ashima Rout1, Srinivas Sethi2
1
Department of ETC, IGIT Sarang, Odisha, India,
Department of CSEA, IGIT Sarang, Odisha, India,
2
ABSTRACT
Cognitive Radio Ad Hoc Network (CRAHN) is a self-organized temporary network in which unlicensed users can
access the spectrum of Primary Users in Primary Network during ideal time period of Primary Users. For this
environment spectrum sensing sharing, management have important role to efficient use of spectrum. Due to this
Quality of Service (QoS) analysis of spectrum is essential. In this paper we analyzed the performance of Spectrum in
term of Throughput.
Keywords: CRAHN; Spectrum Analysis; Throughput;
1. INTRODUCTION
The detection and utilization of the ideal spectrum bands can be achieved by sensing its radio environment in order to
improve the spectrum utilization in cognitive radio ad hoc network(CRAHN), which are bring rigorous challenges and
required functionalities like spectrum sensing, sharing, management and mobility for realization of cognitive radio
[1][2]. The effective utilization of the existing Radio Frequency (RF) spectrum bandwidth usage has been a continuous
scarce resource in wireless domain. The maximum area of spectrum which are licensed to primary services are not in
use include mobile communication system, television broadcasting and satellite communication system etc. This
problem can be solved by effective utilization of spectrum thereby implementing cognitive radio ad hoc network. The
Cognitive Radio (CR) network can be outlined from Software Defined Radio (SDR), in which frequency range,
modulation type or output power can be altered by software without changing the hardware components [1]. SDR and
intelligent signal processing (ISP) are two major technologies associated to define CR where, CR implies ISP at the
physical layer of a wireless system and implementation of CR seems to be quite a hard task without using ISP in these
higher layers. As all the OSI layers need to be flexible for CR network implementation, spectrum efficiency gains may
not be optimized without optimization of all layers.
The CR technology achieves Dynamic Spectrum Access (DSA) [3] of licensed bands of the spectrum by taking the
advantage of spectrum utilization with an access to the unlicensed users and 70% of the allocated spectrum in US is not
utilized the observation of Federal Communications Commission (FCC). It implies the concept of Spectrum reuse
which allows secondary users (SUs) to utilize the radio spectrum licensed to the primary users (PUs). Spectrum
sensing, dynamic spectrum management and adaptive communications are the concept behind Spectrum reuse is
cognitive radio network [4]. The issues on spectrum sharing in CR technology are based on the considerations of
opportunistically allocating licensed channels to a set of cognitive base stations to maximize channel usage. Among the
coexisting CR, dynamic sharing algorithm allows a secondary or cognitive user to utilize the slots previously assigned
to the other active secondary users under particular constraints of probability. In this paper we analyze the spectrum
performance in CRAHN using NS-2 simulator and its CRCN integration [11][12].
The rest of the paper is started with spectrum analysis in section 2, followed by simulation environment in section 3.
Results analysis has been discussed in chapter 4. Finally conclusion is discussed in section 5.
2. SPECTRUM ANALYSIS
Identifies the spectrum availability and adjusts it to the surrounding environment by undergoing different phases like
Spectrum sensing, Spectrum sharing, Spectrum decision, Spectrum analysis and Spectrum mobility is prime feature of
CR and other feature is described as Re-configurability. Re-configurability means CR will configure dynamically
according to the environment and different transmission parameters that can be reconfigured are operating frequency,
bandwidth modulation type and transmission power to opportunistically make use of the available spectrum those are in
Volume 2, Issue 6, June 2013
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International Journal of Application or Innovation in Engineering & Management (IJAIEM)
Web Site: www.ijaiem.org Email: editor@ijaiem.org, editorijaiem@gmail.com
Volume 2, Issue 6, June 2013
ISSN 2319 - 4847
process of changing always [2][4].
The secondary network does not own a license and tries to utilize the spectrum in an opportunistic manner and this
network may or may not have its own base station, as per the architecture [4]. Sensing the radio frequency spectrum
and Channel Identification are the major tasks of CR which detects the spectrum holes is needed at the receiver for
coherent detection and Transmit Power Control. The Dynamic Spectrum Management which selects the transmission
power levels and frequency holes for transmission and the tasks are carried out in the receiver (RX) and the transmitter
(TX) which requires some form of feedback between RX and TX [6].
In Centralized architecture there are two main entities; one is a base station, which schedules the data transmission of
users in the network and the other one is responsible for allocating the radio resource to spectrum broker and also users
where users may be primary, secondary, or both. The spectrum broker may be assigned the task of performing as a
primary/ secondary base station or a dedicated entity dealing with spectrum allocation [8]. The sensed spectrum
information is to create a spectrum allocation map for radio resource allocation. In Distributed CR network there is no
spectrum broker or a base station to coordinate spectrum access of secondary user and the network is divided into
cooperative and non-cooperative networks. In cooperative network, the users share the interference information and
determine spectrum allocation based on this shared information whereas; there is no communication for interference
information in non-cooperative network, which implies the CR users access the spectrum on local policies. In general
comparison Cooperative network is better than non-cooperative network as regards to the system throughput.
Both the users (Primary/Secondary) share same radio channels to communicate with their base stations. In this paper,
we have traced the activities of primary users and then related with secondary users and the given spectrum divided
into the number of channels that are licensed to the primary network. The primary network contains number of primary
users and in the same area, a CR network is deployed which is a collection of number of secondary or cognitive users.
Further, we have taken time activities in the cognitive radio network. The time, in which the primary user is active, the
same time secondary users are idle or inactive. During active time, the primary user transmits the information to the
base station through the channel in the cognitive radio ad hoc network. This means the primary users utilize the
spectrum for a finite time period. In the other hand the secondary users may uses the free channel of primary users
when the primary users are idle and transmit the data through it to destination node.
The activity of primary users, in the given spectrum for a given time periods depending upon the availability of the
channel. If there is no free channel, a primary user will instigate the secondary users (if any) to give up transmission on
the radio channel, otherwise there will be no transmission of data [4]. Hence, the data transmission activities in a given
spectrum for a fixed given time is judged here.
3. SIMULATION ENVIRONMENT
The performances of cognitive radio ad hoc is evaluated by simulations through Network Simulator-2 (NS-2) [11],
based on the Cognitive Radio Cognitive Network (CRCN) integrated simulator [12]. The simulation is carried outs
with random topology. The source node and destination nodes have been considered in CRAHN for work in different
spectrum bands. The number of SUs in the network is varying from 10 to 50 with multipath traffic exists in the
simulation. It has adopted the classical IEEE 802.11b protocol to demonstrate the performance evaluation of routing
protocol and the Simulation Parameters for CRAHN have been carried out the simulation as per table-1.
S.No
1
2
3
4
5
6
7
8
9
10
11
TABLE-1. Simulation Parameters for CRAHN
Parameters
Values
Area size
500m x500 m.
Transmission range
200 m.
Simulation time
50 s.
Nodes speed
5 m/s
Pause times
5 s.
Data rate
5 Kbps
Mobility model
Random any point.
Interference
1
Number of channel
5
Numbers of SU Node 10,20,30,40,50
Numbers of PU Node 5
No. of Simulation
5
Volume 2, Issue 6, June 2013
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International Journal of Application or Innovation in Engineering & Management (IJAIEM)
Web Site: www.ijaiem.org Email: editor@ijaiem.org, editorijaiem@gmail.com
Volume 2, Issue 6, June 2013
ISSN 2319 - 4847
The throughput is an important performance evaluation parameter that can be obtained through the NS2 Trace for IP
QOS (Quality of services). Throughput is the rate at which a network sends receives data. It is a good channel capacity
of net connections and rated in terms bits per second (bit/s).
4. RESULT ANALYSIS
From figure 1 to 5 there is no steady result except figure1. In figure 1 except few times the throughput is giving same
value for all time. In implies that throughput is better for less numbers of SUs. In figure 6 the similar values of
throughput are given. So at a particular time it can’t be compare for throughput for different SUs node size. In figure 7
the throughput values are decrease with number of SUs. So the performance of CRAHN is decrease with increasing the
SUs node size.
Figure 1: Throughput over Time for 10 SUs
Figure 2: Throughput over Time for 20 SUs
Figure 3: Throughput over Time for 30 SUs
Figure4: Throughput over Time for 40 SUs
Figure5: Throughput over Time for 50 SUs
Volume 2, Issue 6, June 2013
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International Journal of Application or Innovation in Engineering & Management (IJAIEM)
Web Site: www.ijaiem.org Email: editor@ijaiem.org, editorijaiem@gmail.com
Volume 2, Issue 6, June 2013
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Figure6: Throughput over Time
Figure7: Throughput over Number of SUs
5. CONCLUSION
Throughput is the rate at which a network sends receives data. It is a good channel capacity of network connections and
rated in terms bits per second (bit/s). We have taken system throughput to measure the channel quality and efficiency in
the cognitive radio ad hoc network for observation and analyzed the system importance of throughput in said network.
For this we have considered the SUs node size varies from 10 to 50 numbers and each time we observed the system
throughput of CRAHN for different SUs node size. We conclude that the quality and efficiencies of spectrum are more
at less SUs node size.
References
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[3] Cuiran Li, Chengshu Li, “Dynamic Channel Selection Algorithm for Cognitive Radios” 4th IEEE International
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Overlay Cognitive Radio Network for TCP: Greed Isn't Good”, IEEE Communication Magazin, pp:57-63 (July
2009).
[5] Yi Song, Jiang Xie, “Performance analysis of spectrum handoff for cognitive radio ad hoc networks without
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[6] VIT RESEARCH REPORT VIT-R-02219-08.
[7] KhalidA Qaraqe, Hasari Celebi, Muneer Mohammad and Sabit Ekin, “Performance Analysis of Ad Hoc Dispersed
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[8] S. Haykin, “Cognitive Radio: Brain-Empowered Wireless Communications” IEEE Journal on Selected Areas in
Communications, vol. 23, No 2, pp: 201 – 220, (Feb. 2005).
[9] I. F. Akyildiz, W.-Y. Lee, M. C. Vuran, and S. Mohanty, \NeXt generation/ dynamic spectrum access/ cognitive
radio wireless networks: A survey," Elsevier Computer Networks, vol. 15, no. 13, , pp. 2127-2159 , (Sept. 2006).
[10]Clancy T, Walker B, “Predictive dynamic spectrum access ,” SDR forum conference, (2006)
[11]Ns-2 Manual, internet draft (2009).
http://www.isi.edu/nsnam/ns/nsdocumentation.html
[12]CRCN integration
http://stuweb.ee.mtu.edu/~ljialian/
Volume 2, Issue 6, June 2013
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International Journal of Application or Innovation in Engineering & Management (IJAIEM)
Web Site: www.ijaiem.org Email: editor@ijaiem.org, editorijaiem@gmail.com
Volume 2, Issue 6, June 2013
ISSN 2319 - 4847
AUTHOR
Rout A, received post graduate degree in the Department of Electronics and Tele-Communication at
Jadavpur University, Kolkota, India, where she was studying Sub-band coding. She works as faculty in the
department of Electronics and Tele-Communication at Indira Gandhi Institute of Technology Sarang, India.
Now she continues her Ph.D. in the field of Cognitive radio network.
Sethi S, has been teaching Computer Science for more than 16 years. He did his Ph.D in the area of routing
in ad-hock network environment. Dr. Sethi has also worked in the sensor and cognitive radio network. Now
he is working as faculty in the Department of Computer Science Engineering and Application at Indira
Gandhi Institute of Technology Sarang, India.
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