We reconsider the problem of joint power control and beamforming design to maximize the weighted sum rate in large and potentially cell-free massive MIMO networks. In contrast to the available short-term methods, where an iterative algorithm is run for every instantaneous channel realization, we derive an iterative algorithm that can be run only sporadically leveraging known channel statistics, with minor performance loss. In addition, our algorithm also applies to the design of non-trivial cooperative beamforming schemes subject to limited sharing of instantaneous channel state information. Furthermore, our algorithm generalizes and outperforms the competing long-term methods from the massive MIMO literature, which are restricted to long-term power control only or to long-term joint power control and large-scale fading decoding design.

翻译：本文重新研究了大规模及潜在无蜂窝大规模MIMO网络中联合功率控制与波束成形设计以最大化加权和速率的问题。与现有短期方法（需针对每个瞬时信道实现运行迭代算法）不同，我们推导出一种可仅利用已知信道统计特性偶发性运行的迭代算法，其性能损失较小。此外，该算法同样适用于设计受限于瞬时信道状态信息有限共享的非平凡协作波束成形方案。进一步地，本算法推广并超越了大规模MIMO文献中的现有长期方法——这些方法仅限于长期功率控制，或仅限于长期联合功率控制与大尺度衰落解码设计。