CSI-aided Robust Neural-based Decoders

In this work
¹
, we investigate the design of neural based channel decoders for the Binary Asymmetric Channel (BAC), which exhibits robustness issues related to training/testing channel parameters mismatch. Rather than enforcing the independence of the trained model to the channel parameter as in our previous work, we show that providing even a coarse (possibly imperfect) quantized CSI to the decoder, allows to build a single robust neural decoder for all values of channel parameters.