2D Unitary ESPRIT Based Super-Resolution Channel Estimation for Millimeter-Wave Massive MIMO with Hybrid Precoding
Anwen Liao, Zhen Gao, Yongpeng Wu, Hua Wang, and Mohamed-Slim Alouini

TL;DR
This paper introduces a super-resolution channel estimation method for mmWave massive MIMO systems using 2D unitary ESPRIT, significantly reducing pilot overhead while accurately estimating channel parameters.
Contribution
It proposes a novel 2D unitary ESPRIT-based scheme that exploits angular sparsity for high-accuracy, low-overhead channel estimation in hybrid precoding mmWave MIMO systems.
Findings
Achieves high-accuracy AoA/AoD estimation
Reduces pilot overhead compared to conventional methods
Successfully reconstructs high-dimensional channels
Abstract
Millimeter-wave (mmWave) massive multiple-input multiple-output (MIMO) with hybrid precoding is a promising technique for the future 5G wireless communications. Due to a large number of antennas but a much smaller number of radio frequency (RF) chains, estimating the high-dimensional mmWave massive MIMO channel will bring the large pilot overhead. To overcome this challenge, this paper proposes a super-resolution channel estimation scheme based on two-dimensional (2D) u- nitary ESPRIT algorithm. By exploiting the angular sparsity of mmWave channels, the continuously distributed angle of arrivals/departures (AoAs/AoDs) can be jointly estimated with high accuracy. Specifically, by designing the uplink training signals at both base station (BS) and mobile station (MS), we first use low pilot overhead to estimate a low-dimensional effective channel, which has the same shift-invariance of…
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Taxonomy
TopicsMillimeter-Wave Propagation and Modeling · Microwave Engineering and Waveguides · Antenna Design and Optimization
