Neural Network MIMO Detection for Coded Wireless Communication with Impairments

In this paper, a neural network based Multiple-Input-Multiple-Output (MIMO) algorithm is presented. The algorithm is specifically designed to be integrated in a coded MIMO-OFDM system, and is based upon projected gradient descent iterations. We combine our model as a part of a modern coded MIMO-OFDM system, and we compare its performance with common MIMO detectors on simulated data, as well as on field data. We also investigated our model’s performance in the presence of several common communication impairments, and demonstrated empirically its robustness. We show empirically that a single trained model is suited for the detection of both coded and uncoded data, with or without impairments, and in the presence of a wide range of tested SNR levels.