This work considers an uplink wireless communication system where multiple users with multiple antennas transmit data frames over dynamic channels. Previous studies have shown that multiple transmit and receive antennas can substantially enhance the sum-capacity of all users when the channel is known at the transmitter and in the case of uncorrelated transmit and receive antennas. However, spatial correlations stemming from close proximity of transmit antennas and channel variation between pilot and data time slots, known as channel aging, can substantially degrade the transmission rate if they are not properly into account. In this work, we provide an analytical framework to concurrently exploit both of these features. Specifically, we first propose a beamforming framework to capture spatial correlations. Then, based on random matrix theory tools, we introduce a deterministic expression that approximates the average sum-capacity of all users. Subsequently, we obtain the optimal values of pilot spacing and beamforming vectors upon maximizing this expression. Simulation results show the impacts of path loss, velocity of mobile users and Rician factor on the resulting sum-capacity and underscore the efficacy of our methodology compared to prior works.

翻译：本文研究了一个上行无线通信系统，其中多个多天线用户通过动态信道传输数据帧。已有研究表明，当发射端已知信道信息且发射与接收天线不相关时，多根发射与接收天线能显著提升所有用户的和容量。然而，若未妥善处理发射天线近距离布设引起的空间相关性，以及导频时隙与数据时隙间的信道变化（即信道老化），这些因素将严重降低传输速率。本文建立了一个可同时利用这两类特性的分析框架：首先提出波束赋形框架以捕捉空间相关性；继而基于随机矩阵理论工具，引入逼近所有用户平均和容量的确定性表达式；最后通过最大化该表达式，获得导频间隔与波束赋形向量的最优值。仿真结果揭示了路径损耗、用户移动速度及莱斯因子对和容量的影响，并验证了相较于既有方法，本文方法论的有效性。