Source and Relay Power Selection Using Biogeography-Based Optimization for Cognitive Radio Systems
In this paper, we present a binary-based low-complexity interference-aware relay selection scheme for a cognitive radio system with one source and multiple relays, using Biogeography-Based Optimization (BBO) algorithm as one of the novel high-performance Evolutionary Algorithms (EAs). We formulate the joint source and relay power allocation as a mixed integer non-linear programming problem, further reduced to an integer programming problem. Optimally relay assignment using the Exhaustive Search Algorithm (ESA) has a high computational complexity that grows exponentially with the number of relays. We applied the BBO-based relay selection scheme with discrete power control at source and relays for the integer programming problem. We present a low-complex migration model for partial immigration-based BBO, and simulation results show that its performance is close to the optimal ESA.