Channel Estimation for Orthogonal Time Frequency Space (OTFS) Massive MIMO

  • Wenqian Shen
  • , Linglong Dai
  • , Shuangfeng Han
  • , I. Chih-Lin
  • , Robert W. Heath

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

17 Citations (Scopus)

Abstract

Orthogonal time frequency space (OTFS) modulation outperforms orthogonal frequency division multiplexing (OFDM) in high-mobility scenarios. One challenge for OTFS massive MIMO is downlink channel estimation due to the required high pilot overhead. In this paper, we propose a 3D structured orthogonal matching pursuit (3D-SOMP) algorithm based channel estimation technique. First, we show that the OTFS MIMO channel exhibits 3D structured sparsity: normal sparsity along the delay dimension, block sparsity along the Doppler dimension, and burst sparsity along the angle dimension. Based on the 3D structured channel sparsity, we then formulate the downlink channel estimation problem as a sparse signal recovery problem. Simulation results show that the proposed 3D-SOMP algorithm can achieve accurate channel state information with low pilot overhead.

Original languageEnglish
Title of host publication2019 IEEE International Conference on Communications, ICC 2019 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538680889
DOIs
Publication statusPublished - May 2019
Event2019 IEEE International Conference on Communications, ICC 2019 - Shanghai, China
Duration: 20 May 201924 May 2019

Publication series

NameIEEE International Conference on Communications
Volume2019-May
ISSN (Print)1550-3607

Conference

Conference2019 IEEE International Conference on Communications, ICC 2019
Country/TerritoryChina
CityShanghai
Period20/05/1924/05/19

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