Hybrid Differential Evolution based Throughput Optimized Cooperative Spectrum Sensing (CSS) in Cognitive Radio Network

Abstract

Cognitive radio network is considered as an eminent technology for dynamic accessing of wireless spectrum. The emergent wireless services like 5G and IoT faces the problem of spectrum scarcity. The shortage of wireless spectrum is mitigated by using the cognitive radio technology. In cognitive radio technology, the unused licensed spectrum is exploited by means of spectrum sensing. In spectrum sensing process, the longer sensing time provides good detection rate, but it will reduce the amount of time for data transmission and hence affects the achievable throughput of a SUs(Secondary Users). Based on sensing time and fusion scheme parameter an optimization problem is formulated to maximize the throughput of SUs. The designed optimization problem is jointly optimized using Hybrid Differential Evolution (HDE) to generate the optimal value of both sensing time and k-parameter of fusion scheme that maximize achievable throughput. The MATLAB based simulation is carried out based on Cognitive Radio (CR) system parameters to validate the robustness of the proposed optimization technique.  From the simulated results, it is inferred that proposed HDE method outperforms traditional optimization techniques like Differential Evolution (DE) and Genetic algorithm (GA) in terms of achievable throughput.