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

## TL;DR

This paper introduces a novel multi-user hybrid precoding framework for dynamic subarrays in mmWave massive MIMO systems, improving energy efficiency and sum rate while maintaining user fairness and reducing computational complexity.

## Contribution

The paper proposes a new hybrid precoding method that optimizes antenna partitioning based on SINR increments, enhancing performance over fixed subarrays and approaching fully-connected architectures.

## Key findings

- Outperforms fixed subarray schemes in energy efficiency and sum rate
- Reduces computational complexity and search space for antenna partitioning
- Achieves higher energy efficiency with minimal sum rate loss compared to fully-connected systems

## Abstract

Dynamic subarray achieves a compromise between sum rate and hardware complexity for 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, multi-user hybrid precoding for the dynamic subarray is intractable to solve as the antenna partitioning would result in the user unfairness and multi-user interference (MUI). 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) firstly selects the multi-user set based on the analog effective channel. And then the antenna partitioning algorithm allocates each antenna element to RF chain according to the maximal increment of the signal to the interference noise ratio (SINR). Finally, the hybrid precoding is optimized for the dynamic subarray architecture. By calculating SINRs on the analog effective channels of the selected users, the antenna partitioning can greatly reduce computation complexity and the size of the search space. Moreover, it also guarantees the user fairness since each antenna element is allocated to acquire the maximal SINR increment of all selected users. \textcolor{blue}{Extensive simulation results demonstrate that both the energy efficiency and sum rate of the proposed solution obviously outperforms that of the fixed subarrays, and obtains higher energy efficiency with slight loss of sum rate compared with the fully-connected architecture.