… , synchronization, channel equalization and iterative decoding is … RESULTS We first evaluate
the detection and decoding … application of deep learning for modulation and channel coding…

… distortion before data demodulation and decoding. In Figure 12.6, the DNN is usually trained
… In this chapter, we first discussed various NN structures and learning methods in order to …

… channel state information, no channel equalization is performed in the DSP approach. The
results … when DPN is applied on all chunks to the case when it is applied to the first chunk and …

… decoding of the intercepted signal. Unfortunately, in these cases, the system designer … IV,
the corresponding results are shown in this section together with discussion. First, we follow the …

… be always built first and employed as an equalizer model, which … deep neural network (FC-DNN)-based
channel estimation, nonlinearity compensation, signal detection, and decoding …

… In this paper, we propose a deep learning based JSCC … We design a decoder structure that
combines deep neural … -clipping, channel estimation and channel equalization to exploit the …

… solve them with a modeldriven deep learning (DL) approach. … is the first of its kind aiming at
jointly solving the blind channel … be utilized by channel decoders, such as the Turbo decoder. …

… [8] considered DNN for joint equalization and decoding of OFDM signal. DNN operates in …
First, we add extra channels to the first layer that capture memory effects of the signal, similarly …

… The dual path network was first introduced in our prior work [42], which we extend in this …
It uses the MMSE equalizer assuming that the channel is known as described in Appendix E…

… a deep learning based joint source channel … a decoder structure shown in Figure 2 bottom
right where explicit signal processing kernels such as channel estimation and equalization are …