… Abstract—Recent research on joint source channel coding (… owing to the employment of
deep learning (DL). However, the … coding and the channel coding rate according to the channel …

… coding steps, that is, joint source-channel coding (JSCC), can achieve lower distortion for a
given finite blocklength than separate source and channel coding [2]… coding, channel coding …

… deep machine learning techniques, we propose an autoencoder-based joint sourcechannel
coding … Gaussian noise (AWGN) channel and Rayleigh fading channel, and comparing the …

… Abstract—Deep learning-based joint source-channel coding (DJSCC) is expected to be a
… of channel adaptability as they are typically trained under specific channel conditions. In this …

… To address these challenges we propose Neural Error Correcting and Source Trimming (NECST)
codes, a deep learning framework for jointly learning to compress and errorcorrect an …

… Our motivation in using deep learning for the joint sourcechannel coding design is that in
many applications, instead of recovering the exact transmitted data, we are interested in …

… channel effects and frequency-selective fading of wireless channels. In this article, we take
the advantage of deep learning approaches to handle the various channel … of channel codes …

… We consider the classical joint source-channel coding (JSCC) problem of transmitting an …
(AWGN) channel. While separately optimizing the source encoder and the channel encoder is …

… -the-art channel codes on a canonical (well known) channel in terms of the … codes obtained
via deep learning which outperforms state-of-the-art codes, signaling a potential shift in code …

… a deep neural network framework for Joint Source-Channel Coding of an m dimensional iid
Gaussian source for transmission over a single additive white Gaussian noise channel with …