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Energy Efficient Power Control for the Two-tier Networks with Small Cells and Massive MIMO

机译:小型双层网络的节能功率控制   小区和大规模mImO

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摘要

In this paper, energy efficient power control for the uplink two-tiernetworks where a macrocell tier with a massive multiple-input multiple-output(MIMO) base station is overlaid with a small cell tier is investigated. Wepropose a distributed energy efficient power control algorithm which allowseach user in the two-tier network taking individual decisions to optimize itsown energy efficiency (EE) for the multi-user and multi-cell scenario. Thedistributed power control algorithm is implemented by decoupling the EEoptimization problem into two steps. In the first step, we propose to assignthe users on the same resource into the same group and each group can optimizeits own EE, respectively. In the second step, multiple power control gamesbased on evolutionary game theory (EGT) are formulated for each group, whichallows each user optimizing its own EE. In the EGT-based power control games,each player selects a strategy giving a higher payoff than the average payoff,which can improve the fairness among the users. The proposed algorithm has alinear complexity with respect to the number of subcarriers and the number ofcells in comparison with the brute force approach which has an exponentialcomplexity. Simulation results show the remarkable improvements in terms offairness by using the proposed algorithm.
机译:本文研究了上行链路两层网络的节能功率控制,在该网络中,具有大规模多输入多输出(MIMO)基站的宏小区层与小小区层重叠。我们提出了一种分布式节能电源控制算法,该算法允许两层网络中的每个用户自行决定,以针对多用户和多小区场景优化自身的能源效率(EE)。分布式电源控制算法是通过将EEoptimization问题分解为两个步骤来实现的。第一步,我们建议将相同资源上的用户分配到同一组中,每个组可以分别优化其自己的EE。第二步,为每个小组制定基于进化博弈论(EGT)的多个功率控制游戏,这使每个用户都可以优化自己的EE。在基于EGT的功率控制游戏中,每个玩家都选择一种收益要高于平均收益的策略,从而可以提高用户之间的公平性。与具有指数复杂度的强力方法相比,所提出的算法在子载波数量和小区数量方面具有线性复杂度。仿真结果表明,该算法在公平性方面有显着的提高。

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