Spatial Denoising for Sparse Channel Estimation in Coherent Massive MIMO

Alexander Osinsky, Andrey Ivanov, Dmitry Yarotsky

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In this paper, we present a new sparse channel estimation (CE) for phase-synchronized sub-6G Massive Multiple-Input Multiple-Output (MIMO) receivers. The algorithm employs an iterative search for propagation channel taps, spatial filtration, and denoising. For that, we split each channel tap signal into tap-aligned and orthogonal parts and train their weighting coefficients in non-line-of-sight channel realizations generated in the QuaDRiGa 2.0 software. Simulation results are presented and compared with the beamspace CE implemented by the digital transformation of the antenna signal to a priori selected subspace directed towards channel taps.

Original languageEnglish
Title of host publication2021 IEEE 94th Vehicular Technology Conference, VTC 2021-Fall - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665413688
DOIs
Publication statusPublished - 2021
Event94th IEEE Vehicular Technology Conference, VTC 2021-Fall - Virtual, Online, United States
Duration: 27 Sep 202130 Sep 2021

Publication series

NameIEEE Vehicular Technology Conference
Volume2021-September
ISSN (Print)1550-2252

Conference

Conference94th IEEE Vehicular Technology Conference, VTC 2021-Fall
Country/TerritoryUnited States
CityVirtual, Online
Period27/09/2130/09/21

Keywords

  • Channel estimation
  • Massive MIMO

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