Multi-Objective Optimal Resource Allocation Using Particle Swarm Optimization in Cognitive Radio

Abstract

In multi-channel ad-hoc cognitive radio networks, each channel has different wireless channel gain and primary activity so that achievable data rate to secondary users (SUs) and required sensing parameter value are channel dependent. SUs also have different energy saving requirements and data traffic demands. In this paper, a dynamic MAC frame configuration and optimal resource allocation scheme for multi-channel ad-hoc cognitive radio network is proposed. We formulate our dynamic resource allocation model as a constrained optimization problem with multi-objective functions using particle swarm optimization (PSO) algorithm. The proposed PSO scheme guarantees that the allocation captures the individual traffic and energy saving demands and maximizes the objectives functions simultaneously.