We propose an algorithm for joint precoding and user selection in multiple-input multiple-output systems with extremely-large aperture arrays, assuming realistic channel conditions and imperfect channel estimates. The use of long-term channel state information (CSI) for user scheduling, and a proper selection of the set of users for which CSI is updated allow for obtaining an improved achievable sum spectral efficiency. We also confirm that the effect of imperfect CSI in the precoding vector design and the cost of training must be taken into consideration for realistic performance prediction.

翻译：我们提出了一种在极大规模孔径阵列多输入多输出系统中，针对实际信道条件和不完美信道估计的联合预编码与用户选择算法。采用长期信道状态信息进行用户调度，并合理选择需要更新CSI的用户集，从而获得更高的可实现总和频谱效率。我们还证实，在实际性能预测中，必须考虑预编码向量设计中不完美CSI的影响以及训练开销。