Joint sparsity pattern learning based channel estimation for massive MIMO-OTFS systems
Joint sparsity pattern learning based channel estimation for massive MIMO-OTFS systems
We propose a channel estimation scheme based on joint sparsity pattern learning (JSPL) for massive multi-input multi-output (MIMO) orthogonal time-frequency-space (OTFS) modulation aided systems. By exploiting the potential joint sparsity of the delay-Doppler-angle (DDA) domain channel, the channel estimation problem is transformed into a sparse recovery problem. To solve it, we first apply the spike and slab prior model to iteratively estimate the support set of the channel matrix, and a higher-accuracy parameter update rule relying on the identified support set is introduced into the iteration. Then the specific values of the channel elements corresponding to the support set are estimated by the orthogonal matching pursuit (OMP) method. Both our simulation results and analysis demonstrate that the proposed JSPL channel estimation scheme achieves an improved performance over the representative state-of-the-art baseline schemes, despite its reduced pilot overhead.
Meng, Kuo
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Yang, Shaoshi
376b9d24-235e-49b6-bf17-302260f7e2be
Wang, Xiao-Yang
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Bu, Yan
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Tang, Yurong
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Zhang, Jinhua
fc9b1f90-33b2-4381-ac93-57e7c79fc10c
Hanzo, Lajos
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August 2024
Meng, Kuo
f54440e2-23b8-4b7f-a291-9b4d75adee82
Yang, Shaoshi
376b9d24-235e-49b6-bf17-302260f7e2be
Wang, Xiao-Yang
6f6e5675-af49-4c06-8abf-2a45a9427fb8
Bu, Yan
cd927263-f468-483d-abcb-3de44bf26251
Tang, Yurong
729b10eb-6d2f-4e57-8680-8decf97155b6
Zhang, Jinhua
fc9b1f90-33b2-4381-ac93-57e7c79fc10c
Hanzo, Lajos
66e7266f-3066-4fc0-8391-e000acce71a1
Meng, Kuo, Yang, Shaoshi, Wang, Xiao-Yang, Bu, Yan, Tang, Yurong, Zhang, Jinhua and Hanzo, Lajos
(2024)
Joint sparsity pattern learning based channel estimation for massive MIMO-OTFS systems.
IEEE Transactions on Vehicular Technology, 73 (8).
(doi:10.1109/TVT.2024.3375027).
Abstract
We propose a channel estimation scheme based on joint sparsity pattern learning (JSPL) for massive multi-input multi-output (MIMO) orthogonal time-frequency-space (OTFS) modulation aided systems. By exploiting the potential joint sparsity of the delay-Doppler-angle (DDA) domain channel, the channel estimation problem is transformed into a sparse recovery problem. To solve it, we first apply the spike and slab prior model to iteratively estimate the support set of the channel matrix, and a higher-accuracy parameter update rule relying on the identified support set is introduced into the iteration. Then the specific values of the channel elements corresponding to the support set are estimated by the orthogonal matching pursuit (OMP) method. Both our simulation results and analysis demonstrate that the proposed JSPL channel estimation scheme achieves an improved performance over the representative state-of-the-art baseline schemes, despite its reduced pilot overhead.
Text
channelestimation
- Accepted Manuscript
More information
Accepted/In Press date: 5 March 2024
e-pub ahead of print date: 18 March 2024
Published date: August 2024
Identifiers
Local EPrints ID: 487868
URI: http://eprints.soton.ac.uk/id/eprint/487868
ISSN: 0018-9545
PURE UUID: 615521fd-7a55-4702-923f-1f7605ff9888
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Date deposited: 07 Mar 2024 17:44
Last modified: 03 Oct 2025 04:01
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Contributors
Author:
Kuo Meng
Author:
Shaoshi Yang
Author:
Xiao-Yang Wang
Author:
Yan Bu
Author:
Yurong Tang
Author:
Jinhua Zhang
Author:
Lajos Hanzo
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