This paper studies the transmit power optimization in multi-cell massive multiple-input multiple-output (MIMO) systems. Network-wide max-min fairness (NW-MMF) and network-wide proportional fairness (NW-PF) are two well-known power control schemes in the literature. The NW-MMF focus on maximizing the fairness among users at the cost of penalizing users with good channel conditions. On the other hand, the NW-PF focuses on maximizing the sum SE, thereby ignoring fairness, but gives some extra attention to the weakest users. However, both of these schemes suffer from a scalability issue which means that for large networks, it is highly probable that one user has a very poor channel condition, pushing the spectral efficiency (SE) of all users towards zero. To overcome the scalability issue of NW-MMF and NW-PF, we propose a novel power control scheme that is provably scalable. This scheme maximizes the geometric mean (GM) of the per-cell max-min SE. To solve this new optimization problem, we prove that it can be rewritten in a convex optimization form and then solved using standard tools. The simulation results highlight the benefits of our model which is balancing between NW-PF and NW-MMF.
翻译:本文研究的是多细胞大规模多投入多产出(MIMO)系统中的输电优化。全网络最大公平(NW-MMF)和全网络比例公平(NW-PF)是文献中广为人知的两种电源控制办法。NW-MMF注重最大限度地提高用户之间的公平性,而以惩罚使用者为代价,同时以良好的频道条件惩罚用户。另一方面,NW-PF注重最大限度地增加SE总和,从而忽视公平性,但给予最弱用户更多的注意。然而,这两个办法都存在一个可扩缩性问题,这意味着对大型网络来说,一个用户的频道状况极差,很可能将所有用户的光谱效率推向零。为了克服NW-MMF和NW-PF的可扩缩性问题,我们提议一个新的电源控制计划是可伸缩的。这个计划最大限度地提高了PSE的几何平均值(GM),从而忽略了这个新的优化问题。为了解决这个新的问题,我们证明它可以重新写出一个模型,即MFMF工具的模拟和模型。