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基于部分可测马尔科夫决策过程业务感知的微基站休眠时长确定策略

陈前斌 何小强 吴攀 唐伦

陈前斌, 何小强, 吴攀, 唐伦. 基于部分可测马尔科夫决策过程业务感知的微基站休眠时长确定策略[J]. 电子与信息学报, 2018, 40(1): 130-136. doi: 10.11999/JEIT170274
引用本文: 陈前斌, 何小强, 吴攀, 唐伦. 基于部分可测马尔科夫决策过程业务感知的微基站休眠时长确定策略[J]. 电子与信息学报, 2018, 40(1): 130-136. doi: 10.11999/JEIT170274
CHEN Qianbin, HE Xiaoqiang, WU Pan, TANG Lun. Micro Base Station Sleeping Cycle Determination Strategy Based on Partially Observed Markov Decision Process Traffic Aware[J]. Journal of Electronics & Information Technology, 2018, 40(1): 130-136. doi: 10.11999/JEIT170274
Citation: CHEN Qianbin, HE Xiaoqiang, WU Pan, TANG Lun. Micro Base Station Sleeping Cycle Determination Strategy Based on Partially Observed Markov Decision Process Traffic Aware[J]. Journal of Electronics & Information Technology, 2018, 40(1): 130-136. doi: 10.11999/JEIT170274

基于部分可测马尔科夫决策过程业务感知的微基站休眠时长确定策略

doi: 10.11999/JEIT170274
基金项目: 

国家高科技研究发展计划(2014AA01A701),国家自然科学基金(61571073)

Micro Base Station Sleeping Cycle Determination Strategy Based on Partially Observed Markov Decision Process Traffic Aware

Funds: 

The National High Technology Research and Development Program of China (2014AA01A701), The National Natural Science Foundation of China (61571073)

  • 摘要: 针对密集组网场景中业务不确定性引起的基站休眠周期难以确定的问题,该文提出一种基于部分可测马尔可夫决策过程(Partially Observed Markov Decision Process, POMDP)业务感知的微基站休眠时长确定策略。该策略将周期分为长周期和短周期,每个周期由轻度和深度两个阶段构成。通过POMDP感知到达基站的业务状态,动态调整周期时长,进而选取适合当前周期的时长。仿真结果表明,该策略可以根据业务感知提前确定微基站关断时长,与基于业务门限值的基站关断机制相比节能效果更好。
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出版历程
  • 收稿日期:  2017-03-31
  • 修回日期:  2017-08-09
  • 刊出日期:  2018-01-19

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