Optimization of Non-convex Cooperative Spectrum Sensing with Modified Artificial Bee Colony Algorithm

This paper investigates multiband cooperative spectrum sensing problem in cognitive radio system aiming at maximizing total opportunistic throughput when the interference to primary users is given. It can be formulated as a combinatorial optimization problem with two different kinds of parameters, weight coefficients and decision thresholds. Due to the non-convex nature of the formulated problem, we first propose an artificial bee colony algorithm (ABC) to solve it. To enhance the searching ability of the algorithm in terms of finding the optimal solution, we further introduce some modifications into the ABC and thus, the modified ABC (MABC) is devised. The simulation results indicate that MABC exhibits a promising performance in dealing with such problems when compared with other intelligence algorithms such as genetic algorithm (GA) and particle swarm optimization (PSO).