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Energy Efficient Spectrum Aware Channel Sensing Routing Protocol for Cognitive Radio Mobile Ad-Hoc Networks

by S. Chinnasamy, R. Vadivel
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 157 - Number 3
Year of Publication: 2017
Authors: S. Chinnasamy, R. Vadivel
10.5120/ijca2017912649

S. Chinnasamy, R. Vadivel . Energy Efficient Spectrum Aware Channel Sensing Routing Protocol for Cognitive Radio Mobile Ad-Hoc Networks. International Journal of Computer Applications. 157, 3 ( Jan 2017), 31-36. DOI=10.5120/ijca2017912649

@article{ 10.5120/ijca2017912649,
author = { S. Chinnasamy, R. Vadivel },
title = { Energy Efficient Spectrum Aware Channel Sensing Routing Protocol for Cognitive Radio Mobile Ad-Hoc Networks },
journal = { International Journal of Computer Applications },
issue_date = { Jan 2017 },
volume = { 157 },
number = { 3 },
month = { Jan },
year = { 2017 },
issn = { 0975-8887 },
pages = { 31-36 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume157/number3/26813-2017912649/ },
doi = { 10.5120/ijca2017912649 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:02:58.369207+05:30
%A S. Chinnasamy
%A R. Vadivel
%T Energy Efficient Spectrum Aware Channel Sensing Routing Protocol for Cognitive Radio Mobile Ad-Hoc Networks
%J International Journal of Computer Applications
%@ 0975-8887
%V 157
%N 3
%P 31-36
%D 2017
%I Foundation of Computer Science (FCS), NY, USA
Abstract

A cognitive radio ad hoc network is the thrust research area in the field of wireless communications. This paper presents the network clustering scheme, the model and algorithm for the clustered cooperative channel sensing based on reinforcement learning. It is imperative to minimize energy cost for channel sensing so as to prolong lifetime of the network. Hence an algorithm for the cooperative channel sensing based on reinforcement learning is proposed. Performance metrics such as success rate, average broadcast delay are taken into account for comparison. Simulation results portrays that the proposed EESACSRP outperforms in terms of the chosen performance metrics.

References
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  2. kyildiz IF, Lee WY, Chowdhury KR. Crahns: Cognitive radio ad hoc networks. AD hoc networks 2009a; 7(5):810–36.
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  5. Rahman M, et al. Cognitive Radio Ad-hoc Networks: A Routing Perspective, 2013.
  6. Yang Qina,∗, Xiaoxiong Zhonga,b, Yuanyuan Yangc, Li Lia, Fangshan Wua,Y. Qin et al., TCPJGNC: A transport control protocol based on network coding for multi-hop cognitive radio networks, Computer Communications (2016).
  7. On-demand routing protocols for cognitive radio ad hoc networks, Shelly Salim and Sangman Moh, EURASIP Journal on Wireless Communications and Networking (2013).
Index Terms

Computer Science
Information Sciences

Keywords

Cognitive Radio Ad Hoc Network Cluster Head Quality of-Services cognitive radio multi-hop architectures

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