首页|期刊导航|高技术通讯（英文版）|An autonomic joint radio resource management algorithm in end-to-end reconfigurable system
高技术通讯（英文版）2008，Vol.14Issue(3)：238-244,7.
An autonomic joint radio resource management algorithm in end-to-end reconfigurable system
An autonomic joint radio resource management algorithm in end-to-end reconfigurable system
摘要
Abstract
This paper presents the multi-step Q-learning (MQL) algorithm as an autonomic approach to the joint radio resource management (JRRM) among heterogeneous radio access technologies (RATs) in the B3G environment.Through the "trial-and-error" on-line learning process, the JRRM controller can converge to the optimized admission control policy.The JRRM controller learns to give the best allocation for each session in terms of both the access RAT and the service bandwidth.Simulation results show that the proposed algorithm realizes the autonomy of JRRM and achieves well trade-off between the spectrum utility and the blocking probability comparing to the load-balancing algorithm and the utility-maximizing algorithm.Besides, the proposed algorithm has better online performances and convergence speed than the one-step Q-learning (QL) algorithm.Therefore, the user statisfaction degree could be improved also.关键词
joint radio resource management/reinforcement learning/autonomic/end-to-end reconfigurabihty/heterogeneous networksKey words
joint radio resource management/reinforcement learning/autonomic/end-to-end reconfigurabihty/heterogeneous networks分类
信息技术与安全科学引用本文复制引用
Lin Yuewei ,Le yanbien,Xue Yuan,Feng Zhiyong,Zhang Yongjing..An autonomic joint radio resource management algorithm in end-to-end reconfigurable system[J].高技术通讯（英文版）,2008,14(3):238-244,7.基金项目
Supported by the National Natural Science Foundation of China (No.60632030) and the National High Technology Research and Development Program of China (No.2006AA01Z276). （No.60632030）
