  We consider the problem of recovering channel code parameters over a
candidate set by merely analyzing the received encoded signals. We propose a
deep learning-based solution that I) is capable of identifying the channel code
parameters for any coding scheme (such as LDPC, Convolutional, Turbo, and Polar
codes), II) is robust against channel impairments like multi-path fading, III)
does not require any previous knowledge or estimation of channel state or
signal-to-noise ratio (SNR), and IV) outperforms related works in terms of
probability of detecting the correct code parameters.
