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.

翻译：我们认为,仅通过分析收到的编码信号,就可以对候选人恢复频道代码参数的问题。 我们提出了一个深层次的基于学习的解决方案,即I(I)能够确定任何编码计划(如LDPC、Convolutional、Turbo和Pollar代码)的频道代码参数,II)对于多路径消退、III等频道缺陷,不需要事先了解或估计频道状态或信号到噪音比率(SNR),而对于探测正确代码参数的概率而言,其相关工作比其他工作要强。