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...

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Bibliographic Details
Published in:IEEE transactions on vehicular technology 2021-09, Vol.70 (9), p.9607-9612
Main Authors: Sui, Zeping, Yan, Shefeng, Zhang, Hongming, Yang, Lie-Liang, Hanzo, Lajos
Format: Article
Language:English
Subjects:
Algorithms
approximate message passing
Bayesian analysis
Complexity
Complexity theory
compressed sensing (CS)
Damping
Detectors
index modulation (IM)
Indexes
Mean square error methods
Mean square errors
Message passing
MMSE
OFDM
Orthogonal Frequency Division Multiplexing
Root-mean-square errors
Signal to noise ratio
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Summary: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.
ISSN:0018-9545
1939-9359
DOI:10.1109/TVT.2021.3101894