Energy Saving Game for Massive MIMO: Coping With Daily Load Variation
Energy Saving Game for Massive MIMO: Coping With Daily Load Variation
复制标题
大规模 MIMO 的节能游戏：应对日常负载变化
DOI：
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发表时间：
2018
影响因子：
6.8
通讯作者：
Riku Jantti
中科院分区：
文献类型：
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作者：
M. M. A. Hossain;C. Cavdar;Emil Bjornson;Riku Jantti
大规模MIMO （MM）是一种领先的技术，可以满足非常高的容量需求。然而，为了应对一天内显著的时间负载变化（TLV）， MM系统的能耗需要具有负载自适应能力。本文提出了一个博弈论模型，用于研究负载自适应多小区大规模MIMO系统，其中每个基站（BS）自适应TLV的天线数量，以最大化下行链路的能量效率（EE）。这里考虑的效用函数定义为每焦耳能量传递的比特数。为了纳入TLV，在假设网络的维度为在峰值负载时服务最大数量的用户的情况下，将每个BS的负载建模为$M/G/ M/ M $状态依赖队列。EE最大化问题是在博弈论框架下制定的，其中通过最佳响应迭代确定BS使用的天线数量。与基线系统相比，这种负载自适应系统的EE提高了24%左右，节省了40%左右的能源，在基线系统中，BSs总是使用固定数量的天线运行，这在峰值负载下是最节能的，当没有流量时可以关闭。
Massive MIMO (MM) is one of the leading technologies that can cater for very high capacity demand. However, energy consumption of MM systems needs to be load adaptive in order to cope with the significant temporal load variations (TLV) over a day. In this paper, we propose a game-theoretic model for studying load adaptive multicell massive MIMO system where each base station (BS) adapts the number of antennas to the TLV in order to maximize the downlink energy efficiency (EE). The utility function considered here is defined as the number of bits transferred per Joule of energy. In order to incorporate the TLV, the load at each BS is modeled as an $M/G/m/m$ state dependent queue under the assumption that the network is dimensioned to serve a maximum number of users at the peak load. The EE maximization problem is formulated in a game theoretic framework where the number of antennas to be used by a BS is determined through the best response iteration. This load adaptive system achieves around 24% higher EE and saves around 40% energy compared to a baseline system where the BSs always run with the fixed number of antennas that is most energy efficient at the peak load and that can be switched off when there is no traffic.