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

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4 Author(s)
Yujun Bao ; Inf. Inst., Southwest Univ. of Sci. & Technol., Mian Yang, China ; Hong Jiang ; Yuqing Huang ; RongChun Hu

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.

Published in:

Computer and Information Science, 2009. ICIS 2009. Eighth IEEE/ACIS International Conference on

Date of Conference:

1-3 June 2009