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Communications technology

Fast Decoding of LDPC Convolutional Codes

Huijuan Zheng

Published Jan 1, 2009• 0 citations
OpenAlex

Abstract

By adopting a serial massage-passing strategy,a modified variant of the original pipeline iterative decoding algorithm is proposed for low-density parity-check (LDPC) convolutional codes. Both analysis and simulation results show that,compared to the original decoding algorithm,the modified algorithm exhibits a much faster convergence speed and could achieve the same performance as the original one by using only one half of the number of processors.

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By adopting a serial massage-passing strategy,a modified variant of the original pipeline iterative decoding algorithm is proposed for low-density parity-check (LDPC) convolutional codes. Both analysis and simulation results show that,compared to the original decoding algorithm,the modified algorithm exhibits a much faster convergence speed and could achieve the same performance as the original one by using only one half of the number of processors.
Abstract: In this paper, a fast-convergence algorithm is proposed for the decoding of low-density parity-check (LDPC) codes. By putting more weight on the message update from check node to variable node in current iteration, the proposed method speeds up the decoding significantly. Simulation results show that compared with the standard layered min-sum decoding algorithm, the proposed scheme may reduce about 1/6 iteration numbers for LDPC codes used in DVB-S2, with hardware complexity overhead less than 2%. Key–Words: LDPC code, fast convergence decoding algorithm, layered decoding, min-sum algorithm, hardware implementation 1
Low-density parity-check (LDPC) codes are one of the most powerful codes known today. They are decoded iteratively by a message passing algorithm. There exist many different update schemes of the exchanged messages. The major difference of all update schemes is the convergence speed, i.e. the achieved communications performance for a limited number of iterations. This paper presents a new decoding algorithm which efficiently utilizes the encoder property of linear encodable LDPC codes. The basic idea is to interpret the LDPC encoder as an encoder with puncturing unit which opens as well the door for hybrid ARQ schemes. The presented new decoding algorithm shows a faster convergence behavior than state of art decoding schemes and it results in a lower error floor
In recent years, the demand for low latency and high reliability in industrial have been increasing rapidly. To meet these requirements, we propose a new decoding architecture of low-density parity-check convolutional codes (LDPC-CC). The proposed decoding architecture reduces the distance of the neighboring processors by using the rationale of compact pipeline decoder. At the same time, the stopping rule is employed in the process of iteration and the weighting factor is added to reduce the error propagation caused by the update of the parity-check node, thus accelerating the convergence of the decoding. The results show that the proposed algorithm has about 0.3 dB gain compared with the on-demand variable node activation (OVA) algorithm when the bit rate error (BER) is 10-4and maximum number of iterations is 10. Meanwhile, the initial delay and storage requirement are reduced by about 50% and the average number of iterations per decoded bit is also reduced largely.