Multi-User Hybrid Precoding for Dynamic Subarrays in mmWave Massive MIMO Systems

Dynamic subarray achieves a compromise between the sum rate and hardware complexity of millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) systems, in which antenna elements are dynamically partitioned to radio frequency (RF) chain according to the channel state information. However, most prior works on multi-user hybrid precoding only considered the fully connected architecture or the fixed subarray architecture. In this paper, a novel multi-user hybrid precoding framework is proposed for the dynamic subarray architecture. Different from the existing schemes, the base station (BS) first selects the multi-user set based on the analog effective channel. Then, the antenna partitioning algorithm allocates each antenna element to the RF chain according to the maximum increment of the signal-to-interference-noise ratio (SINR). Finally, the hybrid precoding is optimized for the dynamic subarray architecture. By calculating the SINRs on the analog effective channels of the selected users, the antenna partitioning can greatly reduce the computation complexity and the size of the search space. Moreover, it also guarantees the user fairness because each antenna element is allocated to acquire the maximum increment of the SINR for all selected users. The extensive simulation results demonstrate that both the energy efficiency and sum rate of the proposed solution obviously outperform those of the fixed subarrays, and the proposed solution obtains higher energy efficiency with a slight loss of sum rate compared with the fully connected architecture.