Design and Analysis of Adaptive Message Coding on LDPC Decoder with Faulty Storage

Abstract

Unreliable message storage severely degrades the performance of LDPC decoders. This paper discusses the impacts of message errors on LDPC decoders and schemes improving the robustness. Firstly, we develop a discrete density evolution analysis for faulty LDPC decoders, which indicates that protecting the sign bits of messages is effective enough for finite-precision LDPC decoders. Secondly, we analyze the effects of quantization precision loss for static sign bit protection and propose an embedded dynamic coding scheme by adaptively employing the least significant bits (LSBs) to protect the sign bits. Thirdly, we give a construction of Hamming product code for the adaptive coding and present low complexity decoding algorithms. Theoretic analysis indicates that the proposed scheme outperforms traditional triple modular redundancy (TMR) scheme in decoding both threshold and residual errors, while Monte Carlo simulations show that the performance loss is less than 0.2 dB when the storage error probability varies from 10 −3 to 10 −4 .

On the Performance of Rate-Compatible LDPC Codes under All-Integer Quantization Decoding

“…Nowadays, it is well known that low-density parity-check (LDPC) codes can provide great error correction performance over many types of communication channels [1][2][3]. Terefore, LDPC codes are chosen for various communication standards, such as DVB-S2 [4], optical fber [5], and 3GPP [6].…”