Volume 18, No. 6, 2021
An Efficient Hybrid Optimization-Based Particle Swarm Optimization & Genetic Algorithm For Cooperative Spectrum Sensing In Cognitive Radio Networks
Jitendra Kumar Mishra , Bhagwat kakde
Abstract
Emerging communication devices need an effective resource allocation approach in wireless communication systems. Cognitive radio networks minimize the bottleneck problem of spectrum scarcity in wireless communication. In wireless communication systems, cognitive radio networks provide the principle of unused licenced spectrum utilization. The cognitive radio network system process accesses spectrum without interfering with the licenced user. The diversity of spectrum sharing and sensing of cognitive radio networks are gaining much attention in wireless communication systems. This paper proposed an efficient hybrid optimization algorithm for the sensing of spectrum without interference. The proposed hybrid optimization algorithm encapsulates particle swarm optimization and genetic algorithms. The objective of the proposed algorithm is to collect information about spectrum on a local level and allocate global units using particle swarm optimization. The diversity of proposed algorithms influences the performance of cognitive radio networks. The proposed algorithm simulates various parameters in terms of throughput using MATLAB tools. The proposed algorithm compares existing algorithms for spectrum sensing and dynamic resource allocation in cognitive radio networks. According to the results, the proposed algorithm outperforms the existing cognitive radio network algorithms by 3–5%.
Pages: 5340-5352
Keywords: CRN, Spectrum Sensing, PSO, GA, Sharing, Dynamic Allocation