In this paper, we investigate the uplink and downlink performance of single cell Massive multiple-input multiple-output (MIMO) system under channel varying conditions due to rapid user mobility. During uplink, the mobile users transmit orthogonal pilot sequences to the base station for channel state information (CSI) estimation prior to data transmission. During downlink, the base station sends orthogonal pilots to the users for estimating the downlink channel before data transmission. In both the cases, the signal to interference and noise ratio (SINR) and mean spectral efficiency are evaluated using suitable numerical analysis. The overall spectral efficiency maximization problem is found to be convex optimization problem consisting of various linear functions and quadratic expressions. By using primal decomposition, the convex problem is transformed into two sub-problems based on frame utilization and resource allocation. For efficient convergence of the sub-problems, a joint resource allocation and user scheduling (JRAUS) algorithm based on resource allocation scheme for frame allotment and user scheduling with matching techniques is proposed. Finally, the simulation results revealed the performance improvement of Massive MIMO network by the use of the proposed JRUAS algorithmic procedure under various conditions.

在本文中，我们研究了由于用户快速移动而在信道变化条件下，单小区大规模多输入多输出（MIMO）系统的上行链路和下行链路性能。在上行链路期间，移动用户在数据传输之前向基站传输正交导频序列，以进行信道状态信息（CSI）估计。在下行链路期间，基站在数据传输之前向用户发送正交导频，以估计下行链路信道。在这两种情况下，均使用适当的数值分析来评估信噪比（SINR）和平均频谱效率。发现总频谱效率最大化问题是由各种线性函数和二次表达式组成的凸优化问题。通过使用原始分解，根据帧利用率和资源分配，将凸问题转化为两个子问题。为了有效地解决子问题，提出了一种基于资源分配方案的联合资源分配和用户调度（JRAUS）算法。最后，仿真结果揭示了通过在各种条件下使用所提出的JRUAS算法程序，可以改善Massive MIMO网络的性能。