Low-Complexity and High-Resolution DOA Estimation for Hybrid Analog and Digital Massive MIMO Receive Array

TL;DR

This paper introduces low-complexity hybrid analog-digital methods for high-resolution DOA estimation in massive MIMO arrays, reducing cost and complexity while maintaining near-optimal accuracy.

Contribution

It proposes novel phase alignment techniques and a fast Root-MUSIC-based method tailored for hybrid arrays, significantly lowering computational complexity compared to traditional approaches.

Findings

Achieves near-CRLB accuracy with reduced complexity

Effectively eliminates spurious solutions via power maximization strategy

Demonstrates superior performance over pure linear search methods

Abstract

A large-scale fully-digital receive antenna array can provide very high-resolution direction of arrival (DOA) estimation, but resulting in a significantly high RF-chain circuit cost. Thus, a hybrid analog and digital (HAD) structure is preferred. Two phase alignment (PA) methods, HAD PA (HADPA) and hybrid digital and analog PA (HDAPA), are proposed to estimate DOA based on the parametric method. Compared to analog phase alignment (APA), they can significantly reduce the complexity in the PA phases. Subsequently, a fast root multiple signal classification HDAPA (Root-MUSIC-HDAPA) method is proposed specially for this hybrid structure to implement an approximately analytical solution. Due to the HAD structure, there exists the effect of direction-finding ambiguity. A smart strategy of maximizing the average receive power is adopted to delete those spurious solutions and preserve the true optimal solution by linear searching over a set of limited finite candidate directions. This results in a significant reduction in computational complexity. Eventually, the Cramer-Rao lower bound (CRLB) of finding emitter direction using the HAD structure is derived. Simulation results show that our proposed methods, Root-MUSIC-HDAPA and HDAPA, can achieve the hybrid CRLB with their complexities being significantly lower than those of pure linear searching-based methods, such as APA.