Mixed-timescale Per-group Hybrid Precoding for Multiuser Massive MIMO Systems

TL;DR

This paper proposes a mixed-timescale hybrid precoding scheme for multiuser massive MIMO systems that improves energy efficiency and reduces hardware costs and signaling overhead using an adaptive partially-connected RF structure.

Contribution

It introduces a novel mixed-timescale per-group hybrid precoding method with an adaptive RF connection network and a heuristic algorithm for near-optimal performance.

Findings

Achieves better energy efficiency than conventional schemes.

Reduces hardware cost and CSI signaling overhead.

Lower computational complexity in precoding design.

Abstract

Considering the expensive radio frequency (RF) chain, huge training overhead and feedback burden issues in massive MIMO, in this letter, we propose a mixed-timescale per-group hybrid precoding (MPHP) scheme under an adaptive partially-connected RF precoding structure (PRPS), where the RF precoder is implemented using an adaptive connection network (ACN) and M analog phase shifters (APSs), where M is the number of antennas at the base station (BS). Exploiting the mixed-time stage channel state information (CSI) structure, the joint-design of ACN and APSs is formulated as a statistical signal-to-leakage-and-noise ratio (SSLNR) maximization problem, and a heuristic group RF precoding (GRFP) algorithm is proposed to provide a near-optimal solution. Simulation results show that the proposed design advances at better energy efficiency (EE) and lower hardware cost, CSI signaling overhead and computational complexity than the conventional hybrid precoding (HP) schemes.