RETRACTED CHAPTER: A Cluster-Based Distributed Cooperative Spectrum Sensing Techniques in Cognitive Radio

Abstract

The optimization techniques are used in various fields to save transmit power with the shortest distances and achieve energy-efficient clusters while restricting interference to primary users. Spectrum sensing among the multi-users grouping in cognitive radio (CR) systems using Distributed Swarm Intelligent-Based Clustering (DSIBC) shows superiority in power saving, convergence time, and sensing error. The proposed DSIBC algorithm is used to develop energy-efficient distributed cluster-based sensing with an optimal number of clusters on their connectivity. In this work, the primary users (PUs) and secondary users (SUs) with random waypoint mobility are considered for implementation. DSIBC has increased the speed of convergence by grouping among multi-users clustered communication than other optimization techniques. The results proved that the reduction in average node power is superior by 9.646% compared to existing in primary nodes. Similarly, DSIBC is superior by 24.231% in SUs average node power. In DSIBC, the detection performance is superior to the existing method. For small signal-to-noise ratio (SNR) <2 dB, the probability of detection is high. In primary detection, the proposed DSIBC is yielding a low false alarm rate compared to other optimized techniques. It is used to solve the problem of multimodal optimization and compare performance with various optimization methods to maximize network bandwidth.