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arXiv · 1812.01571

Multilevel MIMO Detection with Deep Learning

Vincent Corlay·Joseph J. Boutros·Philippe Ciblat·Loïc Brunel
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Abstract

A quasi-static flat multiple-antenna channel is considered. We show how real multilevel modulation symbols can be detected via deep neural networks. A multi-plateau sigmoid function is introduced. Then, after showing the DNN architecture for detection, we propose a twin-network neural structure. Batch size and training statistics for efficient learning are investigated. Near-Maximum-Likelihood performance with a relatively reasonable number of parameters is achieved.

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Vincent Corlay, Joseph J. Boutros, Philippe Ciblat, Loïc Brunel. 2018-12-04. Multilevel MIMO Detection with Deep Learning. https://arxiv.org/abs/1812.01571

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