Self-Calibration for Channel Estimation in Hybrid Millimeter-Wave MIMO Systems

被引：1

作者：

Arai, Kabuto ^{[1
]}

Ishibashi, Koji ^{[1
]}

机构：

[1] Univ Electrocommun, Adv Wireless & Commun Res Ctr AWCC, 1-5-1 Chofugaoka, Tokyo 1828585, Japan

来源：

2023 IEEE 98TH VEHICULAR TECHNOLOGY CONFERENCE, VTC2023-FALL | 2023年

基金：

日本科学技术振兴机构;

关键词：

mmWave; hybrid architecture; channel estimation; self-calibration; array manifold errors; compressed sensing;

D O I：

10.1109/VTC2023-Fall60731.2023.10333598

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper proposes a self-calibration algorithm for a hybrid millimeter-wave (mmWave) multiple-input-multiple-output (MIMO) channel estimation in the presence of array manifold errors composed of mutual coupling, antenna gain/phase errors, and antenna spacing errors due to hardware impairments. The proposed algorithm can jointly estimate angles of arrivals (AoAs), angles of departures (AoDs), path gains, and array mani-fold errors. The initial coarse estimates for AoAs, AoDs, and path gains are derived by a compressed sensing (CS) algorithm without prior knowledge of array manifold errors. Subsequently, AoAs, AoDs, path gains, and array manifold errors are updated based on corresponding maximum likelihood (ML) criteria. Numerical results demonstrate that the proposed algorithm has superior performance with low pilot overhead compared to conventional methods.

引用

页数：5

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