Multilevel MIMO Detection with Deep Learning

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.

To Appear in the Proceedings of the 52nd Annual Asilomar Conference on Signals, Systems, and Computers

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• Learning to Detect
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Cited by in corpus (1)

• Learning to Search for MIMO Detection