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A Low-Complexity Large-MIMO Approximate Message Passing Detector
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DOI：10.1109/TVT.2023.3344872.png)
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Abstract
En 中文
Message passing algorithms (MPAs) are iterative algorithms widely used in multiple-input multiple-output (MIMO) detection, benefiting from their good trade-off between performance and complexity. In this paper, a low-complexity large-MIMO approximate message passing (LC-LAMA) detector with partial message updates is proposed. Also, we propose an evolutionary algorithm (EA) based method to optimize the number of updated messages in LC-LAMA for multiple scenarios. Numerical results exhibit that the proposed LC-LAMA detector presents comparable performance to that of state-of-the-art (SOA) detectors. The superior performance of LC-LAMA in mismatch scenarios illustrates its robustness. An analysis of complexity reveals the proposed LC-LAMA provides at most 72.7% complexity reduction as compared to other SOA detectors.
Keywords:
Detectors
MIMO communication
Complexity theory
Optimization
Message passing
Transmitting antennas
Evolutionary computation
Multiple-input multiple-output (MIMO) detector
approximate message passing
partial message updates
evolutionary algorithm (EA)
Journal
IF:
7.1
Papers:
1.8W
Citations:
6.6W