Optimal resource allocation for transmission diversity in multi-radio access networks:a coevolutionary genetic algorithm approach

作     者：FAN WenHao LIU YuanAn WU Fan 

作者机构：Beijing Key Laboratory of Work Safety Intelligent MonitoringBeijing University of Posts and Telecommunications Wireless Communications and EMC LaboratorySchool of Electronic EngineeringBeijing University of Posts and Telecommunications 

出 版 物：《Science China(Information Sciences)》 (中国科学:信息科学(英文版))

年 卷 期：2014年第57卷第2期

页      面：99-112页

核心收录：

学科分类：0810[工学-信息与通信工程] 080904[工学-电磁场与微波技术] 0808[工学-电气工程] 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] 081001[工学-通信与信息系统] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：supported by National Science and Technology Major Project(Grant Nos.2010ZX03002-005-02,2012ZX03001-001-002) National Natural Science Foundation of China(Grants Nos.61003279,60973111) Technology Project of Guangdong Province(2011B090400433) Director Foundation of Beijing Key Laboratory of Work Safety Intelligent Monitoring 

主　　题：multi-radio access radio resource management multi-radio transmission diversity Lagrangian method coevolutionary algorithm genetic algorithm 

摘      要：The next generation wireless communication systems aim at supporting enhanced diversified network access and data transmission abilities via the cooperative integration and unified management of various radio access technologies(RATs).The resource allocation is the core component leading the network system and mobile terminals to the service robustness and performance *** this paper,a numeric optimization model for optimizing terminals’transmission power and allocated RAT bandwidth for maximizing system capacity is proposed with the focal consideration of the multi-radio transmission diversity for parallel transmission through multiple links from diferent RATs,and diferent terminal characteristics on RAT ***,we design a centralized and periodic scheduling algorithm including an improved coevolutionary genetic algorithm for efciently solving the optimization *** results demonstrate that our propose algorithm can distinctly enhance the system performance and improve the computational efciency.