This letter focuses on the pilot contamination problem in the uplink and downlink of cell-free massive multiple-input multiple-output networks with different degrees of cooperation between access points. The optimum minimum mean square error processing can take advantage of large-scale fading coefficients for canceling the interference of pilot-sharing user-equipments and thus achieves asymptotically unbounded capacity. However, it is computationally demanding and can only be implemented in a fully centralized network. Here, sub-optimal schemes are derived that provide unbounded capacity with linear-growing complexity and using only local channel estimates but global channel statistics. This makes them suited for both centralized and distributed networks. In this latter case, the best performance is achieved with a generalized maximum ratio combiner that maximizes a capacity bound based on channel statistics only.
翻译:本信侧重于无细胞的大型多投入多产出网络的上链和下链中的试验污染问题,这些网络在接入点之间合作程度不同。最佳的最小平均平方错误处理可以利用大规模下降系数来取消试点共享用户设备干扰,从而实现无限制能力。然而,它具有计算性要求,只能在完全集中的网络中实施。这里,生成的次最佳计划提供无限制能力,线性复杂性增加,仅使用本地频道估计数据,但使用全球频道统计数据。这使得它们适合集中和分布的网络。在后一种情况下,最佳的绩效是通过普遍的最大比率组合实现,使仅以频道统计数据为主的容量最大化。