Energy Efficient Switch Policy for Small Cells

被引:15
作者
Gan Xiaoying [1 ,2 ]
Wang Luyang [1 ]
Feng Xinxin [1 ]
Liu Jing [1 ]
Yu Hui [1 ]
Zhang Zhizhong [3 ]
Liu Haitao [3 ]
机构
[1] Shanghai Jiao Tong Univ, Dept Elect Engn, Shanghai 200030, Peoples R China
[2] Xidian Univ, State Key Lab Integrated Serv Networks, Xian, Peoples R China
[3] Philips Res China, Lighting Dept, Shanghai, Peoples R China
基金
中国国家自然科学基金;
关键词
heterogeneous network; small cell; switch policy; Q-learning;
D O I
10.1109/CC.2015.7084385
中图分类号
TN [电子技术、通信技术];
学科分类号
0809 ;
摘要
Switch policy is essential for small cells to properly serve variable number of users in an energy efficient way. However, frequently switching small cell base stations (SBSs) may increase the network operating cost, especially when there is an nonnegligible start-up energy cost. To this end, by observing the variety of user number, we focus on the design of a switch policy which minimize the cumulative energy consumption. A given user transmission rate is guaranteed and the capability of SBSs are limited as well. According to the knowledge on user number variety, we classify the energy consumption problem into two cases. In complete information case, to minimize the cumulative energy consumption, an offline solution is proposed according to critical segments. A heuristic algorithm for incomplete information case (HAIIC) is proposed by tracking the difference of cumulative energy consumption. The upper bound of the Energy Consumption Ratio (ECR) for HAIIC is derived as well. In addition, a practical Q-learning based probabilistic policy is proposed. Simulation results show that the proposed HAIIC algorithm is able to save energy efficiently.
引用
收藏
页码:78 / 88
页数:11
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