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Energy-Efficient Cluster-Based Cooperative Spectrum Sensing in a Multiple Antenna Cognitive Radio Network

Samson I. Ojo 1, Zachaeus K. Adeyemo 1, Damilare O. Akande 1, and Ayobami O. Fawole 2
1. Electronic and Electrical Engineering Department, Ladoke Akintola University of Technology, Ogbomoso, Nigeria
2. Electronic and Electrical Engineering Department, The Polytechnic Ibadan, Ibadan, Nigeria

Abstract—Spectrum Hole Detection (SHD) is a major operation in a Cognitive Radio (CR) network to identify empty spectrum for maximum utilization. However, SHD is often affected by multipath effects resulting in interference. The existing techniques used to address these problems are faced by poor detection rate, long sensing time and bandwidth inefficiency. Hence, this paper proposes a cluster-based Energy-Efficient Multiple Antenna Cooperative Spectrum Sensing (EEMACSS) for SHD in CR networks using Energy Detector (ED) with a modified combiner. Multiple secondary users are used to carry out local sensing using ED in multiple antenna configurations. The local sensing results are combined at the cluster head using majority fusion rule to determine the sensing results at each cluster. The sensing results from individual cluster are combined to determine the global sensing result using OR fusion rule. The proposed EEMACSS is evaluated using Probability of Detection (PD), Sensing Time (ST) and Spectral Efficiency (SE) by comparing with existing techniques. The results reveal that the proposed technique shows better performance.

Index Terms—Cluster, Cooperative Spectrum Sensing (CSS), Energy Detector (ED), Multiple Antenna (MA), Primary User (PU), Secondary User (SU)

Cite: Samson I. Ojo, Zachaeus K. Adeyemo, Damilare O. Akande, and Ayobami O. Fawole, "Energy-Efficient Cluster-Based Cooperative Spectrum Sensing in a Multiple Antenna Cognitive Radio Network," International Journal of Electrical and Electronic Engineering & Telecommunications, Vol. 10, No. 3, pp. 176-185, May 2021. Doi: 10.18178/ijeetc.10.3.176-185

Copyright © 2021 by the authors. This is an open access article distributed under the Creative Commons Attribution License (CC BY-NC-ND 4.0), which permits use, distribution and reproduction in any medium, provided that the article is properly cited, the use is non-commercial and no modifications or adaptations are made.