BEACHES: Beamspace Channel Estimation for Multi-Antenna mmWave Systems and Beyond

被引：5

作者：

Ghods, Ramina ^{[1
]}

Gallyas-Sanhueza, Alexandra ^{[1
]}

Mirfarshbafan, Seyed Hadi ^{[1
]}

Studer, Christoph ^{[1
]}

机构：

[1] Cornell Univ, Sch Elect & Comp Engn, Ithaca, NY 14850 USA

来源：

2019 IEEE 20TH INTERNATIONAL WORKSHOP ON SIGNAL PROCESSING ADVANCES IN WIRELESS COMMUNICATIONS (SPAWC 2019) | 2019年

基金：

美国国家科学基金会;

关键词：

MILLIMETER-WAVE COMMUNICATIONS; MIMO;

D O I：

10.1109/spawc.2019.8815576

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Massive multi-antenna millimeter wave (mmWave) and terahertz wireless systems promise high-bandwidth communication to multiple user equipments in the same time-frequency resource. The high path loss of wave propagation at such frequencies and the fine-grained nature of beamforming with massive antenna arrays necessitates accurate channel estimation to fully exploit the advantages of such systems. In this paper, we propose BEAmspace CHannel EStimation (BEACHES), a low-complexity channel estimation algorithm for multi-antenna mmWave systems and beyond. BEACHES leverages the fact that wave propagation at high frequencies is directional, which enables us to denoise the (approximately) sparse channel state information in the beamspace domain. To avoid tedious parameter selection, BEACHES includes a computationally-efficient tuning stage that provably minimizes the mean-square error of the channel estimate in the large-antenna limit. To demonstrate the efficacy of BEACHES, we provide simulation results for line-of-sight (LoS) and non-LoS mmWave channel models.

引用

页数：5