This article studies a novel distributed precoding design, coined team minimum mean-square error (TMMSE) precoding, which rigorously generalizes classical centralized MMSE precoding to distributed operations based on transmitter-specific channel state information (CSIT). Building on the so-called theory of teams, we derive a set of necessary and sufficient conditions for optimal TMMSE precoding, in the form of an infinite dimensional linear system of equations. These optimality conditions are further specialized to cell-free massive MIMO networks, and explicitly solved for two important examples, i.e., the classical case of local CSIT and the case of unidirectional CSIT sharing along a serial fronthaul. The latter case is relevant, e.g., for the recently proposed radio stripe concept and the related advances on sequential processing exploiting serial connections. In both cases, our optimal design outperforms the heuristic methods that are known from the previous literature. Duality arguments and numerical simulations validate the effectiveness of the proposed team theoretical approach in terms of ergodic achievable rates under a sum-power constraint.
翻译:这篇文章研究的是新颖的分布式预先编码设计,创下团队最小平均差错(TMMSE)预编码,严格地将传统的中央中央MMSE预编码化为基于特定发报机频道状态信息的分布式操作(CSIT ) 。基于所谓的团队理论,我们为最佳的TMMSE预编码制定了一套必要和充分的条件,其形式是无限的线性线性方程系统。这些最佳条件进一步专业化,成为无细胞大型MIMO网络,并为两个重要例子明确解答,即当地CSIT的典型案例和在连续前厅进行单向中央CSIT共享的案例。后一个案例具有相关性,例如,最近提出的无线电条概念以及利用序列连接进行连续处理的相关进展。在这两个案例中,我们的最佳设计都超越了从以前的文献中知道的超光学方法。质量论点和数字模拟证实了拟议的团队理论方法在总力制约下可实现的热量率方面的有效性。