SNR MXM in relay selection in cognitive radio using heuristic techniques

日期 : Sep 2015 - Jun 2016

Cognitive Radio (CR) is one of the prime candidate technology to increase the spectral efficiency of an underutilized wireless spectrum.The idea behind a Cognitive Radio Network (CRN) is to look for unused channels (holes) in wireless spectrum of licensed users (called Primary Users) and dynamically assigns them to unlicensed users (called Secondary User). For practical scenarios where the source and destination are far apart, one may have to deploy several relays, such a network is called multi-relay CRNs. A well-planned CRNs may provide improved spectral efficiency, by using dynamic spectrum access techniques, as well as better coverage and all time connectivity to end users. However, it raises several critical design and performance issues. The optimization problem under consideration is non-relay selection scenario, where a single source is trying to communicate with Secondary User (SU) in the presence of Primary User (PU) through relayed cognitive radio network under power and interference constraints. Heuristic techniques are extensively adopted by researchers to solve the optimization problems. Three well known heuristic techniques: “Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and Differential Evolution (DE)” are applied to this aforesaid problem. Results have shown that PSO outperforms the GA and DE in attaining the max SNR at SU.