Policy Optimization for Content Push via Energy Harvesting Small Cells in Heterogeneous Networks

被引:33
作者
Gong, Jie [1 ]
Zhou, Sheng [2 ]
Zhou, Zhenyu [3 ]
Niu, Zhisheng [2 ]
机构
[1] Sun Yat Sen Univ, Sch Data & Comp Sci, Guangzhou 510006, Guangdong, Peoples R China
[2] Tsinghua Univ, Tsinghua Natl Lab Informat Sci & Technol, Dept Elect Engn, Beijing 100084, Peoples R China
[3] North China Elect Power Univ, State Key Lab Alternate Elect Power Syst Renewabl, Sch Elect & Elect Engn, Beijing 102206, Peoples R China
关键词
Content caching and push; dynamic programming; energy harvesting; heterogeneous networks; small cell; COMMUNICATION;
D O I
10.1109/TWC.2016.2628789
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Motivated by the rapid development of energy harvesting technology and content-aware communication in access networks, this paper considers the push mechanism design in small-cell base stations (SBSs) powered by renewable energy. A user request can be satisfied by either push or unicast from the SBS. If the SBS cannot handle the request, the user is blocked by the SBS and is served by the macro-cell BS instead, which typically consumes more energy. We aim to minimize the ratio of user requests blocked by the SBS to total number of user requests. With finite battery capacity, Markov decision process-based problem is formulated, and the optimal policy is found by dynamic programming (DP). Two threshold-based policies are proposed: the push-only threshold-based policy and the energy-efficient threshold-based policy, and the closed-form blocking probabilities with infinite battery capacity are derived. Numerical results show that the proposed policies outperform the conventional non-push policy if the content popularity changes slowly or the content request generating rate is high, and can achieve the performance of the greedy optimal threshold-based policy. In addition, the performance gap between the threshold-based policies and the DP optimal policy is small when the energy arrival rate is low or the request generating rate is high.
引用
收藏
页码:717 / 729
页数:13
相关论文
共 37 条
[1]  
[Anonymous], 1985, NUMERICAL ANAL
[2]  
Bastug E., 2014, P 11 INT S WIR COMM, P41
[3]   Living on the Edge: The Role of Proactive Caching in 5G Wireless Networks [J].
Bastug, Ejder ;
Bennis, Mehdi ;
Debbah, Merouane .
IEEE COMMUNICATIONS MAGAZINE, 2014, 52 (08) :82-89
[4]  
Bertsekas D., 2012, Dynamic Programming and Optimal Control. Athena Scientific optimization and computation series, VVolume 1
[5]  
Blasco P, 2014, IEEE ICC, P1897, DOI 10.1109/ICC.2014.6883600
[6]  
Cha M, 2007, IMC'07: PROCEEDINGS OF THE 2007 ACM SIGCOMM INTERNET MEASUREMENT CONFERENCE, P1
[7]   Opportunistic Channel Access and RF Energy Harvesting in Cognitive Radio Networks [J].
Dinh Thai Hoang ;
Niyato, Dusit ;
Wang, Ping ;
Kim, Dong In .
IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, 2014, 32 (11) :2039-2052
[8]   Femtocaching and Device-to-Device Collaboration: A New Architecture for Wireless Video Distribution [J].
Golrezaei, Negin ;
Molisch, Andreas F. ;
Dimakis, Alexandros G. ;
Caire, Giuseppe .
IEEE COMMUNICATIONS MAGAZINE, 2013, 51 (04) :142-149
[9]  
Gong J, 2015, IEEE ICC, P25, DOI 10.1109/ICC.2015.7248293
[10]   Base Station Sleeping and Resource Allocation in Renewable Energy Powered Cellular Networks [J].
Gong, Jie ;
Thompson, John S. ;
Zhou, Sheng ;
Niu, Zhisheng .
IEEE TRANSACTIONS ON COMMUNICATIONS, 2014, 62 (11) :3801-3813