CMDNet: Learning a Probabilistic Relaxation of Discrete Variables for Soft Detection With Low Complexity
IEEE Transactions on Communications(2021)
摘要
Following the great success of Machine Learning (ML), especially Deep Neural Networks (DNNs), in many research domains in 2010s, several ML-based approaches were proposed for detection in large inverse linear problems, e.g., massive MIMO systems. The main motivation behind is that the complexity of Maximum A-Posteriori (MAP) detection grows exponentially with system dimensions. Instead of using DN...
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关键词
Complexity theory,MIMO communication,Probabilistic logic,Decoding,Optimization,Detectors,Computational modeling
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