Hybrid Cooperative Energy Detection Techniques in Cognitive Radio Networks

Abstract

Cognitive Radio (CR) has emerged as a smart solution to spectrum bottleneck faced by current wireless services under which licensed spectrum is made available to unlicensed Secondary Users (SUs) through robust and efficient Spectrum Sensing (SS). Energy Detection (ED) is the dominantly used SS approach owing to its low computational complexity and ability to identify spectrum holes without requiring a priori knowledge of primary transmission characteristics. In this chapter, the authors present an in-depth analysis of the ED test statistic. Based on the double threshold ED, they analyze the performance of a Hybrid PSO-OR (Particle Swarm Optimization and OR) algorithm for cooperative SS. The sensing decision of “fuzzy” SUs is optimized using PSO and the final collective decision is made based on OR rule. The idea of using two thresholds is introduced to reduce the communication overhead in reporting local data/decision to the fusion center, which also offers reduced energy consumption. The Hybrid PSO-OR algorithm is shown to exhibit significant performance gain over the Hybrid EGC-OR algorithm.