This paper considers a cell-free massive multiple-input multiple-output network (cfm-MIMO) with a massive number of access points (APs) distributed across an area to deliver information to multiple users. Based on only local channel state information, conjugate beamforming is used under both proper and improper Gaussian signalings. To accomplish the mission of cfm-MIMO in providing fair service to all users, the problem of power allocation to maximize the geometric mean (GM) of users’ rates (GM-rate) is considered. A new scalable algorithm, which iterates linear-complex closed-form expressions and thus is practical regardless of the scale of the network, is developed for its solution. The problem of quality-of-service (QoS) aware network energy-efficiency is also addressed via maximizing the ratio of the GM-rate and the total power consumption, which is also addressed by iterating linear-complex closed-form expressions. Intensive simulations are provided to demonstrate the ability of the GM-rate based optimization to achieve multiple targets such as a uniform QoS, a good sum rate, and a fair power allocation to the APs.

中文翻译：

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无细胞大规模 MIMO 中的可扩展用户速率和能效优化

本文考虑了一种无蜂窝大规模多输入多输出网络 (cfm-MIMO)，该网络具有分布在一个区域内的大量接入点 (AP)，以将信息传递给多个用户。仅基于本地信道状态信息，在适当和不适当的高斯信令下都使用共轭波束成形。为了完成cfm-MIMO为所有用户提供公平服务的使命，考虑了最大化用户速率的几何平均（GM）（GM-rate）的功率分配问题。开发了一种新的可扩展算法，该算法迭代线性复杂的封闭形式表达式，因此无论网络规模如何都是实用的。服务质量 (QoS) 感知网络能效问题也通过最大化 GM 速率与总功耗的比率来解决，这也可以通过迭代线性复数封闭形式表达式来解决。提供了密集的模拟以证明基于 GM 速率的优化能够实现多个目标，例如统一的 QoS、良好的总速率和对 AP 的公平功率分配。