%0 Journal Article
%T A Q-learning Based Autonomic Joint Radio Resource Management Algorithm<br>基于Q学习的自主联合无线资源管理算法
%A Zhang Yong-jing
%A Feng Zhi-yong
%A Zhang Ping
%A <br>张永靖
%A 冯志勇
%A 张平
%J 电子与信息学报
%D 2008
%I 
%X A Q-learning based Joint Radio Resource Management (JRRM) algorithm is proposed for the autonomic resource optimization in a B3G system with heterogeneous Radio Access Technologies (RAT). Through the “trial-and-error” interactions with the radio environment, the JRRM controller learns to allocate the proper RAT and the service bandwidth for each session. A backpropagation neural network is adopted to generalize the large input state space to reduce memory requirement. Simulation results show that the proposed algorithm not only realizes the autonomy of JRRM through the online learning process, but also achieves well trade-off between the spectrum utility and the blocking probability.
%K Radio Access Technology (RAT)
%K Joint admission control
%K Bandwidth allocation
%K Q-learning
%K Neural network<br>无线接入技术(RAT)
%K 联合接纳控制
%K 带宽分配
%K Q学习
%K 神经网络
%K 在线学习
%K 无线资源管理算法
%K Algorithm
%K Radio
%K Resource
%K Management
%K Joint
%K 性能
%K 阻塞率
%K 频谱
%K 自主化
%K 仿真结果
%K 状态空间
%K 输入
%K 神经网络
%K 反向传播
%K 存储需求
%K 带宽
%K 业务
%K 接入技术
%K 配合
%K 会话
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=1319827C0C74AAE8D654BEA21B7F54D3&jid=EFC0377B03BD8D0EF4BBB548AC5F739A&aid=E8E02D4468CF4407DCCD92DB30121484&yid=67289AFF6305E306&vid=340AC2BF8E7AB4FD&iid=38B194292C032A66&sid=5AE7FA263C8A6D65&eid=34D13857B558254E&journal_id=1009-5896&journal_name=电子与信息学报&referenced_num=0&reference_num=11