Low Complexity Overloaded MIMO Non-Linear Detector with Iterative LLR Estimation

This paper proposes a non-linear overloaded MIMO detector that outperforms the conventional soft-input maximum likelihood detector (MLD) with less computational complexity. We propose iterative log-likelihood ratio (LLR) estimation and multi stage LLR estimation for the proposed detector to achieve...

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Bibliographic Details
Published in:IEICE Transactions on Communications 2024/03/01, Vol.E107.B(3), pp.339-348
Main Authors: DENNO, Satoshi, MAKABE, Shuhei, HOU, Yafei
Format: Article
Language:English
Subjects:
Complexity
complexity reduction
Likelihood ratio
MIMO communication
noise cancellation
non-linear detector
ordering
Orthogonal Frequency Division Multiplexing
overloaded MIMO
Overloading
soft-input decoding
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Summary:This paper proposes a non-linear overloaded MIMO detector that outperforms the conventional soft-input maximum likelihood detector (MLD) with less computational complexity. We propose iterative log-likelihood ratio (LLR) estimation and multi stage LLR estimation for the proposed detector to achieve such superior performance. While the iterative LLR estimation achieves better BER performance, the multi stage LLR estimation makes the detector less complex than the conventional soft-input maximum likelihood detector (MLD). The computer simulation reveals that the proposed detector achieves about 0.6dB better BER performance than the soft-input MLD with about half of the soft-input MLD's complexity in a 6×3 overloaded MIMO OFDM system.
ISSN:0916-8516
1745-1345
DOI:10.23919/transcom.2023EBP3118