Energy Efficient Out-of-Band Candidate Channel Sensing Using Particle Swarm Optimization 


Vol. 44,  No. 1, pp. 30-37, Jan.  2019
10.7840/kics.2019.44.1.30


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  Abstract

In this paper, we propose a cooperative out-of-band channel sensing scheme for cognitive radio ad-hoc network so that secondary user (SU) can immediately switch to the new channel if the primary user (PU) appears in currently used channel. We dedicate specific slots for solely sensing purpose so that all available candidate channels can be sensed satisfying required minimum probability of detection. Furthermore, residual energy of each sensing node is also considered to ensure nodes do not die off fast. A utility based optimization problem is formulated to increase probability of detection while reducing number of required slots allocated for sensing and total energy consumption as well as prolong the lifetime of nodes with lower residual energy. Using particle swarm optimization (PSO), we show the superior performance of the proposed scheme in comparison with other schemes.

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  Cite this article

[IEEE Style]

A. P. Shrestha, S. Yoo, J. Kim, J. Choi, S. B. Um, J. W. Choi, "Energy Efficient Out-of-Band Candidate Channel Sensing Using Particle Swarm Optimization," The Journal of Korean Institute of Communications and Information Sciences, vol. 44, no. 1, pp. 30-37, 2019. DOI: 10.7840/kics.2019.44.1.30.

[ACM Style]

Anish Prasad Shrestha, Sang-Jo Yoo, Joung-Sik Kim, Jae-Kark Choi, Soo Bin Um, and Jeung Won Choi. 2019. Energy Efficient Out-of-Band Candidate Channel Sensing Using Particle Swarm Optimization. The Journal of Korean Institute of Communications and Information Sciences, 44, 1, (2019), 30-37. DOI: 10.7840/kics.2019.44.1.30.

[KICS Style]

Anish Prasad Shrestha, Sang-Jo Yoo, Joung-Sik Kim, Jae-Kark Choi, Soo Bin Um, Jeung Won Choi, "Energy Efficient Out-of-Band Candidate Channel Sensing Using Particle Swarm Optimization," The Journal of Korean Institute of Communications and Information Sciences, vol. 44, no. 1, pp. 30-37, 1. 2019. (https://doi.org/10.7840/kics.2019.44.1.30)

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pISSN : 1226 - 4717
eISSN : 2287 - 3880