We consider multi-group multicast precoding designs for cell-free massive multiple-input multiple-output (MIMO) systems. To optimize the transmit and receive beamforming strategies, we focus on minimizing the sum of the maximum mean squared errors (MSEs) over the multicast groups, which is then approximated with the sum MSE to simplify the computation and signaling. We adopt an iterative bi-directional training scheme with uplink and downlink precoded pilots to cooperatively design the multi-group multicast precoders at each base station and the combiners at each user equipment in a distributed fashion. An additional group-specific uplink training resource is introduced, which entirely eliminates the need for backhaul signaling for channel state information (CSI) exchange. We also propose a simpler distributed precoding design based solely on group-specific pilots, which can be useful in the case of scarce training resources. Numerical results show that the proposed distributed methods greatly outperform conventional cell-free massive MIMO precoding designs that rely solely on local CSI.
翻译:我们考虑为无细胞的大规模多投入多输出(MIMO)系统制定多组多组预先编码设计。为了优化传输和接收波束成型战略,我们侧重于最大限度地减少多播组的最大平均正方差(MSEs)的总和,然后将之与MSE总和相近,以简化计算和信号。我们采用了一个迭代双向培训计划,配有上下行连接预码试点,以合作设计每个基地站的多组多组多投多输出预译器和每个用户设备的组合。我们引入了额外的群体专用上行培训资源,这完全消除了频道状态信息交换的反向信号需要。我们还提议了一个仅以特定群体试点为基础的更简单分布的预码设计,这在培训资源稀缺的情况下是有用的。数字结果显示,拟议的分配方法大大超出了完全依赖本地 CSI的常规无细胞巨型MIMO预码设计。