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

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

doi:10.1109/TSP.2019.2919411

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 journal › Article › peer-review

307 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 language	English
Article number	8727425
Pages (from-to)	4204-4217
Number of pages	14
Journal	IEEE Transactions on Signal Processing
Volume	67
Issue number	16
DOIs	https://doi.org/10.1109/TSP.2019.2919411
Publication status	Published - 15 Aug 2019

Keywords

OTFS
channel estimation
high-mobility
massive MIMO
sparsity

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10.1109/TSP.2019.2919411

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Shen, W., Dai, L., An, J., Fan, P., & Heath, R. W. (2019). Channel Estimation for Orthogonal Time Frequency Space (OTFS) Massive MIMO. IEEE Transactions on Signal Processing, 67(16), 4204-4217. Article 8727425. https://doi.org/10.1109/TSP.2019.2919411

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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.",

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author = "Wenqian Shen and Linglong Dai and Jianping An and Pingzhi Fan and Heath, {Robert W.}",

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

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