Massive MIMO-OFDM Channel Acquisition with Multi-group Adjustable Phase Shift Pilots

TL;DR

This paper introduces multi-group adjustable phase shift pilots (MAPSPs) for massive MIMO-OFDM systems, reducing channel estimation overhead and improving spectral efficiency by exploiting channel sparsity and optimized pilot scheduling.

Contribution

The paper extends adjustable phase shift pilots to multiple groups, proposing MAPSPs with a novel design, interference analysis, and implementation scheme to enhance channel estimation and spectral efficiency.

Findings

MAPSP achieves lower MSE than APSP

Significantly improves spectral efficiency in mobility scenarios

Effective pilot interference mitigation through phase scheduling

Abstract

Massive multiple-input multiple-output - orthogonal frequency division multiplexing (MIMO-OFDM) systems face the challenge of high channel acquisition overhead while providing significant spectral efficiency (SE). Adjustable phase shift pilots (APSPs) are an effective technique to acquire channels with low overhead by exploiting channel sparsity. In this paper, we extend it to multiple groups and propose multi-group adjustable phase shift pilots (MAPSPs) to improve SE further. We first introduce a massive MIMO-OFDM system model and transform the conventional channel model in the space-frequency domain to the angle-delay domain, obtaining a sparse channel matrix. Then, we propose a method of generating MAPSPs through multiple basic sequences and investigate channel estimation processes. By analyzing the components of pilot interference, we elucidate the underlying mechanism by which interference affects MMSE estimation. Building upon this foundation, we demonstrate the benefit of phase scheduling in MAPSP channel estimation and establish the optimal design condition tailored for scheduling. Furthermore, we propose an implementation scheme based on Zadoff-Chu sequences that includes received signal pre-processing and pilot scheduling methods to mitigate pilot interference. Simulation results indicate that the MAPSP method achieves a lower mean square error (MSE) of estimation than APSP and significantly enhances SE in mobility scenarios.