Quantum-inspired bacterial foraging algorithm for parameter adjustment in green cognitive radio

作     者：Hongyuan Gao Chenwan Li 

作者机构：School of Information and Communication Engineering Harbin Engineering University 

出 版 物：《Journal of Systems Science & Complexity》 (系统科学与复杂性学报（英文版）)

年 卷 期：2015年第28卷第5期

页      面：897-907页

核心收录：

学科分类：080904[工学-电磁场与微波技术] 0810[工学-信息与通信工程] 07[理学] 0809[工学-电子科学与技术（可授工学、理学学位）] 08[工学] 080402[工学-测试计量技术及仪器] 0804[工学-仪器科学与技术] 070201[理学-理论物理] 081001[工学-通信与信息系统] 0702[理学-物理学] 

基　　金：supported by the National Natural Science Foundation of China(61102106) the China Postdoctoral Science Foundation(2013M530148) the Heilongjiang Postdoctoral Fund(LBH-Z13054) the Fundamental Research Funds for the Central Universities(HEUCF140809) 

主　　题：green cognitive radio parameter adjustment quantumcomputing bacterial foraging algorithm 

摘      要：Parameter adjustment that maximizes the energy efficiency of cognitive radio networks is studied in this paper where it can be investigated as a complex discrete optimization problem. Then a quantum-inspired bacterial foraging algorithm(QBFA)is proposed. Quantum computing has perfect characteristics so as to avoid local convergence and speed up the optimization of QBFA. A proof of convergence is also given for this *** superiority of QBFA is verified by simulations on three test functions. A novel parameter adjustment method based on QBFA is proposed for resource allocation of green cognitive radio. The proposed method can provide a globally optimal solution for parameter adjustment in green cognitive radio networks. Simulation results show the proposed method can reduce energy consumption effectively while satisfying different quality of service(Qo S)requirements.