Multi-objective Optimization of Power Control and Resource Allocation for Cognitive Wireless Networks


Resource optimization is a very important aspect in cognitive radio network (CRN). It is a typical multi-objective optimization problem. This paper proposes a mixed multi-objective immune cloning genetic algorithm (MMGA) to solve the optimization of resource allocation in CRNs. Based on the genetic algorithm of non-domination sort, the MMGA adds external memory immune operator and cloning operator to effectively improve the searching performance. To evaluate the performance of MMGA, we compare it to NSGA-II with three typical test functions. From the results, the MMGA can solve multi-objective optimization problems more effectively than the NSGA-II. Simultaneously, the MMGA is used to optimize the frequency bandwidths and bandwidth-footprint product in CRNs. The simulation results show that MMGA can effectively solve the optimization of resource allocation in CRNs.