Energy-Efficient Hybrid Analog and Digital Precoding for MmWave MIMO Systems With Large Antenna Arrays

TLDR

Hybrid analog‑digital precoding is expected to be used in mmWave MIMO to reduce energy consumption, but fully connected architectures require many phase shifters and are energy‑intensive. This work targets a more energy‑efficient hybrid precoding scheme with a subconnected architecture and proposes a successive interference cancellation (SIC)–based design that achieves near‑optimal performance at low complexity. The SIC approach decomposes the nonconvex rate‑optimization problem into per‑subantenna subrate problems and implements a low‑complexity algorithm that avoids singular‑value decomposition and matrix inversion. The proposed SIC‑based hybrid precoder attains near‑optimal performance, reduces complexity to about 10 % of spatially sparse precoding, and delivers higher energy efficiency than both spatially sparse and fully digital precoding.

Abstract

Millimeter wave (mmWave) MIMO will likely use hybrid analog and digital precoding, which uses a small number of RF chains to reduce the energy consumption associated with mixed signal components like analog-to-digital components not to mention baseband processing complexity. However, most hybrid precoding techniques consider a fully connected architecture requiring a large number of phase shifters, which is also energy-intensive. In this paper, we focus on the more energy-efficient hybrid precoding with subconnected architecture, and propose a successive interference cancelation (SIC)-based hybrid precoding with near-optimal performance and low complexity. Inspired by the idea of SIC for multiuser signal detection, we first propose to decompose the total achievable rate optimization problem with nonconvex constraints into a series of simple subrate optimization problems, each of which only considers one subantenna array. Then, we prove that maximizing the achievable subrate of each subantenna array is equivalent to simply seeking a precoding vector sufficiently close (in terms of Euclidean distance) to the unconstrained optimal solution. Finally, we propose a low-complexity algorithm to realize SIC-based hybrid precoding, which can avoid the need for the singular value decomposition (SVD) and matrix inversion. Complexity evaluation shows that the complexity of SIC-based hybrid precoding is only about 10% as complex as that of the recently proposed spatially sparse precoding in typical mmWave MIMO systems. Simulation results verify that SIC-based hybrid precoding is near-optimal and enjoys higher energy efficiency than the spatially sparse precoding and the fully digital precoding.