… We compare the performance of our deep learning encoder and decoder with a separate
source and channel coding design1. Since the channel considered here is the erasure channel…

… of a neural network based channel encoder (… the channel coding and modulation in an
end-to-end manner, we demonstrate that TurboAE-MOD performs comparable to modern codes …

… 1: The figure shows our channel coding approach. We train an approximation of the mutual
informationIθ(Xn; Y n) between the channel input and output samples (xn,yn), which is used …

… The coded bits are modulated and transmitted over a noisy channel. At the receiver, a noisy
… for the field of machine learning. But using NN for channel coding is special because we …

… , TurboAE) – the first channel coding scheme with both encoder and decoder … art channel
codes under AWGN channels for a moderate block length. We demonstrate that channel coding…

… first channel code to reach the Shannon bound was not invented until 2009, where the
channel … In Table 14.1, we summarize the history of different channel coding schemes and their …

… We focused on the five main challenges that 5G entails: channel coding, massive MIMO,
non-… , in channel coding, deep learning will greatly reduce the time complexity of LDPC codes …

… the compression and channel coding stages. Using machine learning techniques, we investigate
… from scratch, thus using joint source-channel coding (JSCC) rather than the separation …

… However, the decoding algorithm for turbo codes is … of using Deep Learning (DL) architectures
based on Recurrent Neural Networks (RNNs) for encoding and decoding of turbo codes. …

… deteriorates heavily when the code length increases and the … the deep learning methods
to determine whether the intercepted Gaussian noisy signal contains the target channel code …