A massive MIMO network can serve ten’s of users simultaneously. However, in dense scenarios the users are potentially closely-spaced, potentially resulting in substantial inter-user interference. Scheduling can overcome this by selecting the users that lead to the highest combined spectral efficiency. As scheduling comes with a significant pilot overhead, an alternative strategy could minimize user correlation by distributing the antenna elements in space. In this paper, we propose a comprehensive system study including antenna topology and distribution, user scheduling and pilot overhead reduction. Our user scheduling and pilot reduction algorithms are evaluated using system level simulations relying on indoor line-of-sight channel measurements from a 64 antenna base station at 2.61GHz. To have a thorough evaluation of the proposed algorithm, we consider four different antenna topologies, including co-located and distributed placement of the base station arrays. Our evaluation shows that in a conference room with 64 densely deployed users, our proposed low complexity algorithm can improve the spectral efficiency by at least 14% compared to random user selection with the best antenna distribution strategy. Finally, our results show that by relying on channel hardening, we reduce the pilot overhead by 3.2 $\times$ .

中文翻译：

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密集大规模 MIMO 网络中的用户调度和天线拓扑：一项实验研究

一个大规模 MIMO 网络可以同时为数十个用户提供服务。然而，在密集场景中，用户可能间隔很近，可能会导致大量用户间干扰。调度可以通过选择导致最高组合频谱效率的用户来克服这个问题。由于调度伴随着显着的导频开销，替代策略可以通过在空间中分布天线单元来最小化用户相关性。在本文中，我们提出了一个全面的系统研究，包括天线拓扑和分布、用户调度和导频开销减少。我们的用户调度和导频减少算法使用系统级模拟进行评估，该模拟依赖于来自 2.61GHz 的 64 天线基站的室内视距信道测量。为了对所提出的算法进行彻底的评估，我们考虑了四种不同的天线拓扑结构，包括基站阵列的协同定位和分布式布置。我们的评估表明，在具有 64 个密集部署用户的会议室中，与具有最佳天线分布策略的随机用户选择相比，我们提出的低复杂度算法可以将频谱效率提高至少 14%。最后，我们的结果表明，依靠信道强化，我们将导频开销减少了 3.2 $\times$ 。