Particle Swarm Optimization Based Methodology for Solving Network Selection Problem in Cognitive Radio Networks

Measurements by regulatory bodies has revealed in the last decade that due to fixed spectrum assignment to different network operators has led to the temporal and spatial inefficient spectrum utilization. This underutilization of the most portion of the frequency band under different network operators has created opportunities for the secondary/cognitive radio users to access these unused frequency bands. While accessing the licensed spectrum opportunistically secondary user needs to avoid the harmful interference with the licensed/primary users. When there are multiple primary networks with spare spectrum, secondary user has the option of selecting any of these networks, this is referred to as the network selection problem. This paper presents a novel particle swarm optimization algorithm for network selection problem. This study aims to achieve higher throughput for the secondary users with reduced cost as well as less interference incurred by the licensed users. The experimental results manifest that the proposed method is effective in finding near optimal solution.