Blind Recognition of Channel Codes via Deep Learning

Abstract

This paper considers the blind recognition of channel codes from noisy received signal. Specifically, based on the residual neural network (ResNet), the recurrent neural network (RNN), and the attention mechanism, three types of recognizers are proposed to recognize the type of a channel code through a classification process. Other code parameters (e.g., code rate and length) can be recognized by similar ways. Numerical experiments show that the proposed recognizers perform well even when the training set is a very small subset of all possible codewords.