Cell-free massive MIMO communications is an emerging network technology for 5G wireless communications wherein distributed multi-antenna access points (APs) serve many users simultaneously. Most prior work on cell-free massive MIMO systems assume time-division duplexing mode, although frequency-division duplexing (FDD) systems dominate current wireless standards. The key challenges in FDD massive MIMO systems are channel-state information (CSI) acquisition and feedback overhead. To address these challenges, we exploit the so-called angle reciprocity of multipath components in the uplink and downlink, so that the required CSI acquisition overhead scales only with the number of served users, and not the number of AP antennas nor APs. We propose a low complexity multipath component estimation technique and present linear angle-of-arrival (AoA)-based beamforming/combining schemes for FDD-based cell-free massive MIMO systems. We analyze the performance of these schemes by deriving closed-form expressions for the mean-square-error of the estimated multipath components, as well as expressions for the uplink and downlink spectral efficiency. Using semi-definite programming, we solve a max-min power allocation problem that maximizes the minimum user rate under per-user power constraints. Furthermore, we present a user-centric (UC) AP selection scheme in which each user chooses a subset of APs to improve the overall energy efficiency of the system. Simulation results demonstrate that the proposed multipath component estimation technique outperforms conventional subspace-based and gradient-descent based techniques. We also show that the proposed beamforming and combining techniques along with the proposed power control scheme substantially enhance the spectral and energy efficiencies with an adequate number of antennas at the APs.

中文翻译：

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基于 FDD 的无小区大规模 MIMO 系统的高效角域处理

无蜂窝大规模 MIMO 通信是一种用于 5G 无线通信的新兴网络技术，其中分布式多天线接入点 (AP) 同时为多个用户提供服务。尽管频分双工 (FDD) 系统主导着当前的无线标准，但大多数关于无蜂窝大规模 MIMO 系统的先前工作都采用时分双工模式。FDD 大规模 MIMO 系统的主要挑战是信道状态信息 (CSI) 获取和反馈开销。为了应对这些挑战，我们利用了上行链路和下行链路中所谓的多径分量的角度互易性，以便所需的 CSI 获取开销仅随服务用户的数量而变化，而不是 AP 天线或 AP 的数量。我们提出了一种低复杂度的多径分量估计技术，并为基于 FDD 的无小区大规模 MIMO 系统提出了基于线性到达角 (AoA) 的波束成形/组合方案。我们通过推导估计多径分量均方误差的闭式表达式以及上行链路和下行链路频谱效率的表达式来分析这些方案的性能。使用半定规划，我们解决了最大-最小功率分配问题，该问题在每用户功率约束下最大化最小用户速率。此外，我们提出了一种以用户为中心 (UC) 的 AP 选择方案，其中每个用户选择一个 AP 子集来提高系统的整体能效。仿真结果表明，所提出的多径分量估计技术优于传统的基于子空间和基于梯度下降的技术。我们还表明，所提出的波束成形和组合技术以及所提出的功率控制方案通过 AP 上足够数量的天线显着提高了频谱和能量效率。