In this paper, we propose a class of high-efficiency deep joint source-channel coding methods that can closely adapt to the source distribution under nonlinear transform, it be collected name transform (NTSCC). considered model, transmitter first learns analysis map data into latent space, then transmits representation receiver via coding. Our model incorporates as strong prior effectively extr...

The robustness property can be added to DSC system at the expense of reducing performance, i.e., increasing the sum-rate. The aim of designing robust DSC schemes is to trade off between system robustness and compression efficiency. In this paper, after deriving an inner bound on the rate–distortion region for the quadratic Gaussian MDC based RDSC system with two encoders, the structure of...

Source vs. Channel coding • Source coding: represent the source information with the minimum of symbols • Channel coding: represent the source information in a manner that minimizes the error probability in decoding

Two common source-channel coding strategies, tandem coding and channel-optimized quantization, are compared on the basis of distortion vs. complexity by analyzing specific representatives of each when transmitting analog data samples across a binary symmetric channel. Transform coding is used in each strategy, and Reed-Solomon codes are added to form the tandem code. For each strategy, formulas...