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Approximate message passing algorithms for low complexity OFDM-IM detection

Approximate message passing algorithms for low complexity OFDM-IM detection
Approximate message passing algorithms for low complexity OFDM-IM detection
Low complexity approximate message passing (AMP) orthogonal frequency division multiplexing combined with index modulation (OFDM-IM) detection algorithms are proposed, which exploit the sparse structure of the frequency domain (FD) OFDM-IM symbols. To circumvent the high root mean square error (RMSE) in the conventional AMP algorithm, a minimum mean square error (MMSE) denoiser is proposed based on the classic Bayesian approach and on the state evolution of AMP. Our simulation results demonstrate that it is capable of improving both the RMSE as well as the convergence rate. However, in practice, the channel's diagonal FD matrix may be a non-Gaussian sensing matrix, hence a damping strategy is conceived. In conclusion, the proposed MMSE denoiser based damping-assisted AMP-aided detector strikes a compelling bit error ratio vs. complexity trade-off.
approximate message passing, compressed sensing (CS), index modulation (IM), MMSE, OFDM
0018-9545
9607-9612
Sui, Zeping
8f7f0ffc-1264-44b2-bdd5-1a47b119e78a
Yan, Shefeng
9d4ebf69-539c-450f-913f-6bb9d96bdf60
Zhang, Hongming
ebd930db-9cd8-43ff-8b73-92c1d7f0108b
Yang, Lie Liang
ae425648-d9a3-4b7d-8abd-b3cfea375bc7
Hanzo, Lajos
66e7266f-3066-4fc0-8391-e000acce71a1
Sui, Zeping
8f7f0ffc-1264-44b2-bdd5-1a47b119e78a
Yan, Shefeng
9d4ebf69-539c-450f-913f-6bb9d96bdf60
Zhang, Hongming
ebd930db-9cd8-43ff-8b73-92c1d7f0108b
Yang, Lie Liang
ae425648-d9a3-4b7d-8abd-b3cfea375bc7
Hanzo, Lajos
66e7266f-3066-4fc0-8391-e000acce71a1

Sui, Zeping, Yan, Shefeng, Zhang, Hongming, Yang, Lie Liang and Hanzo, Lajos (2021) Approximate message passing algorithms for low complexity OFDM-IM detection. IEEE Transactions on Vehicular Technology, 70 (9), 9607-9612. (doi:10.1109/TVT.2021.3101894).

Record type: Article

Abstract

Low complexity approximate message passing (AMP) orthogonal frequency division multiplexing combined with index modulation (OFDM-IM) detection algorithms are proposed, which exploit the sparse structure of the frequency domain (FD) OFDM-IM symbols. To circumvent the high root mean square error (RMSE) in the conventional AMP algorithm, a minimum mean square error (MMSE) denoiser is proposed based on the classic Bayesian approach and on the state evolution of AMP. Our simulation results demonstrate that it is capable of improving both the RMSE as well as the convergence rate. However, in practice, the channel's diagonal FD matrix may be a non-Gaussian sensing matrix, hence a damping strategy is conceived. In conclusion, the proposed MMSE denoiser based damping-assisted AMP-aided detector strikes a compelling bit error ratio vs. complexity trade-off.

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More information

Published date: 4 August 2021
Additional Information: Funding Information: Manuscript received June 8, 2021; revised July 15, 2021; accepted July 30, 2021. Date of publication August 4, 2021; date of current version September 17, 2021. This work was supported in part by the National Science Foundation of China under Grants 61725106 and 62001056, and in part by the China Scholarship Council under Grant 202004910653. The work of Lajos Hanzo was supported by the European Research Council’s Advanced Fellow Grant QuantCom under Grant 789028. The review of this article was coordinated by Prof. Jia-Chin Lin. (Corresponding author: Shefeng Yan.) Zeping Sui and Shefeng Yan are with the Institute of Acoustics, Chinese Academy of Sciences, Beijing 100190, China, and also with the University of Chinese Academy of Sciences, Beijing 100049, China (e-mail: suizeping@mail.ioa.ac.cn; sfyan@ieee.org). Publisher Copyright: © 1967-2012 IEEE. Copyright: Copyright 2021 Elsevier B.V., All rights reserved.
Keywords: approximate message passing, compressed sensing (CS), index modulation (IM), MMSE, OFDM

Identifiers

Local EPrints ID: 456431
URI: http://eprints.soton.ac.uk/id/eprint/456431
ISSN: 0018-9545
PURE UUID: 6a26c6b8-690f-4b9c-bd5f-7a0308b0117b
ORCID for Lie Liang Yang: ORCID iD orcid.org/0000-0002-2032-9327
ORCID for Lajos Hanzo: ORCID iD orcid.org/0000-0002-2636-5214

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Date deposited: 28 Apr 2022 16:46
Last modified: 19 Jul 2022 01:38

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Contributors

Author: Zeping Sui
Author: Shefeng Yan
Author: Hongming Zhang
Author: Lie Liang Yang ORCID iD
Author: Lajos Hanzo ORCID iD

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