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

By Wenqian Shen, Linglong Dai, Jianping An, P. Fan, Robert W. Heath. ICC 2019 - 2019 IEEE International Conference on Communications (ICC), 2019

430 citations recorded by the source corpus.

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.

Subfields: Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/4158dadaca7ddca2dcf87eb1c6d02545daba1d80

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In Electrical and Electronic Engineering

Citations in the corpus

Orthogonal Time-Frequency Space Modulation: A Promising Next-Generation Waveform (2021, background): “…the Doppler domain of wireless channels allows us to separate the propagation paths experiencing an identical delay and thus fully discloses the available channel DoF. propagation environment having few moving scatterers is considered, the DD domain channel exhibits a sparse response [5].”
On the Effectiveness of OTFS for Joint Radar Parameter Estimation and Communication (2020, neutral): “An efficient pilot-aided CSI acquisition is a problem of independent interest that we postpone to future work (see also [26], [27], [44]).”
Off-grid Channel Estimation with Sparse Bayesian Learning for OTFS Systems (2021, methodology): “The proposed 1D off-grid SBLbased scheme can achieve the most accurate channel estimates compared with the state-of-the-art schemes in the literature [6], [9], [12], [14], [15] at the cost of a higher computational complexity.”