Meta Learning-Based MIMO Detectors: Design, Simulation, and Experimental Test

Deep neural networks (NNs) have exhibited considerable potential for efficiently balancing the performance and complexity of multiple-input and multiple-output (MIMO) detectors. However, existing NN-based MIMO detectors are difficult to be deployed in practical systems because of their slow converge...

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Veröffentlicht in:	IEEE transactions on wireless communications 2021-02, Vol.20 (2), p.1122-1137
Hauptverfasser:	Zhang, Jing, He, Yunfeng, Li, Yu-Wen, Wen, Chao-Kai, Jin, Shi
Format:	Artikel
Sprache:	eng
Schlagworte:	Artificial neural networks Channels Computer simulation Damping Decoding Detectors Distance learning expectation propagation Iterative algorithms Machine learning meta learning MIMO communication MIMO detector Modules Neural networks Online instruction over-the-air platform Parameter sensitivity Receivers Robustness Sensors Signal detection Training turbo receiver
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