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

Wenqian Shen*, Linglong Dai, Jianping An, Pingzhi Fan, Robert W. Heath

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

259 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 large number of base station antennas. In this paper, we propose a 3D-structured orthogonal matching pursuit algorithm based channel estimation technique to solve this problem. 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 algorithm can achieve accurate channel state information with low pilot overhead.

Original languageEnglish
Article number8727425
Pages (from-to)4204-4217
Number of pages14
JournalIEEE Transactions on Signal Processing
Volume67
Issue number16
DOIs
Publication statusPublished - 15 Aug 2019

Keywords

  • OTFS
  • channel estimation
  • high-mobility
  • massive MIMO
  • sparsity

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