Neural Network-Like LDPC Decoder for Mobile Applications

This paper presents a low complexity iterative de coder for Low-Density Parity-Check (LDPC) codes for mobile applications using a Neural Network-like (NNL) structure and a modified Single-Layer Perceptron (SLP) training algorithm.The proposed approach allows for midrange decoding performance with a minimum gap to Shannon-limit of 3.19 dB at a frame error rate of 10-4 for the short frame and the code rate 13/15 of the next-generation Digital Terrestrial Television Broadcasting (DTTB) standard of the Advanced Television Systems Committee (ATSC), the "ATSC 3.0".The NNL decoder has a low decoding time, thus, it would be suitable for low power embedded systems, software-defined radio implementation tools, and software-based DTTB receptors.