密集天线部署的下行性能:是分散还是集中?

Mounia Hamidouche, Ejder Bastug, Jihong Park, L. Cottatellucci, M. Debbah
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引用次数: 1

摘要

大规模多输入多输出(Massive MIMO)和小蜂窝密集化是互补的5G关键推动因素。在单位面积上整个基站天线数量固定的情况下,本文比较:(1)部署少量基站,将多根天线集中在每个基站上,即大规模MIMO;(2)部署较多基站,配备较少天线,即小小区致密化。我们观察到,当每个基站通过L个子频段(多载波传输)服务多个用户时,小基站密度在信号干扰比(SIR)覆盖范围和能量效率(EE)方面总是优于小基站密度。此外,我们还观察到,更大的L增加了SIR覆盖,同时降低了EE,从而迫切需要优化5G网络设计。这两个观测结果是基于我们使用随机几何的新型封闭式SIR覆盖概率推导,也通过数值模拟进行了验证。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Downlink performance of dense antenna deployment: To distribute or concentrate?
Massive multiple-input multiple-output (massive MIMO) and small cell densification are complementary key 5G enablers. Given a fixed number of the entire basestation antennas per unit area, this paper fairly compares (i) to deploy few base stations (BSs) and concentrate many antennas on each of them, i.e. massive MIMO, and (ii) to deploy more BSs equipped with few antennas, i.e. small cell densification. We observe that small cell densification always outperforms for both signal-to-interference ratio (SIR) coverage and energy efficiency (EE), when each BS serves multiple users via L number of sub-bands (multicarrier transmission). Moreover, we also observe that larger L increases SIR coverage while decreasing EE, thus urging the necessity of optimal 5G network design. These two observations are based on our novel closed-form SIR coverage probability derivation using stochastic geometry, also validated via numerical simulations.
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