… Abstract—Recently, semantic communication has been brought to the forefront because
deep learning (DL)-based methods, such as Transformer, have achieved great success in …

… application of deep learning methods to the problem of low complexity channel decoding. A
… To the best of the authors’ knowledge, our deep learning methodology constitutes the first …

… source coding and channel coding are two separate steps. Nowadays, joint sourcechannel
coding … Recently, the deep learning based joint source-channel coding method [14] has been …

… a severe degradation in channel coding gain. On … channel codes with more redundancy
or adding retransmission techniques, which increases the latency. Channel code with low code …

… of a Space Time Block Code (STBC) scheme for 2x1 system … end learning MIMO
communication system as a Deep Neural … for each channel entry and learn 2v discrete channel …

… Further, in [18] we first introduced the idea of exploiting binary codes for tackling mmWave
channel estimation. In particular, we exploit the capability of error discovery of channel codes …

… learning, or mutual information estimation to overcome the need of a known channel model
… it to secure channel coding schemes by sampling the legitimate channel and additionally …

… More explicitly, first of all, we design the MC-AE independently of both the channel coding
arrangement and of the channel model, where the output layer of the MC-AE decoder is …

… Additionally, deep learning combined with reinforcement learning … for the outstanding results
of Deep Learning models: … Error correcting codes for channel coding are used in order to …

… -Channel Coding: Typical source coding mainly utilizes the sparse property to remove the
redundancy in source data while channel coding … that source coding and channel coding can …