Abstract: Most of the existing user scheduling algorithms are based on the incoherence of Multiple Input Multiple Output (MIMO) channels, while there may be coherence among channels in practical systems. Meanwhile, in the Multi-user MIMO (MU-MIMO) system, in order to reduce the overhead of the uplink channel, the user only needs to feedback part of Channel State Information (CSI) to the base station, so the multi-user interference is inevitable. This paper analyzes the influence of the coherence conditions of MIMO channels on the upper limit of user capacity and transmission rates, and then deduces the low-complexity transmission rate based on the residual interference caused by limited feedback. For MU-MIMO limited feedback systems with channel coherence, a user selection method based on reinforcement learning is proposed. The proposed selection method can avoid recalculating the achievable rate in each cycle, thus greatly reducing the computational complexity. When the system is in the coherent channel environment, the proposed algorithm improves the throughput.

Key words: Multi-user MIMO, Limited feedback, Channel coherence, Reinforcement learning, User selection