Sequential decoding

About: Sequential decoding is a research topic. Over the lifetime, 8667 publications have been published within this topic receiving 204271 citations.

High throughput low-density parity-check decoder architectures

Abstract: Two decoding schedules and the corresponding serialized architectures for low-density parity-check (LDPC) decoders are presented. They are applied to codes with parity-check matrices generated either randomly or using geometric properties of elements in Galois fields. Both decoding schedules have low computational requirements. The original concurrent decoding schedule has a large storage requirement that is dependent on the total number of edges in the underlying bipartite graph, while a new, staggered decoding schedule which uses an approximation of the belief propagation, has a reduced memory requirement that is dependent only on the number of bits in the block. The performance of these decoding schedules is evaluated through simulations on a magnetic recording channel.

Implementation aspects of LDPC convolutional codes

Abstract: Potentially large storage requirements and long initial decoding delays are two practical issues related to the decoding of low-density parity-check (LDPC) convolutional codes using a continuous pipeline decoder architecture. In this paper, we propose several reduced complexity decoding strategies to lessen the storage requirements and the initial decoding delay without significant loss in performance. We also provide bit error rate comparisons of LDPC block and LDPC convolutional codes under equal processor (hardware) complexity and equal decoding delay assumptions. A partial syndrome encoder realization for LDPC convolutional codes is also proposed and analyzed. We construct terminated LDPC convolutional codes that are suitable for block transmission over a wide range of frame lengths. Simulation results show that, for terminated LDPC convolutional codes of sufficiently large memory, performance can be improved by increasing the density of the syndrome former matrix.

Iterative soft decoding of Reed-Solomon codes

Abstract: This letter presents an iterative decoding method for Reed-Solomon (RS) codes. The proposed algorithm is a stochastic shifting based iterative decoding (SSID) algorithm which takes advantage of the cyclic structure of RS codes. The performances of different updating schemes are compared. Simulation results show that this method provides significant gain over hard decision decoding and is superior to some other popular soft decision methods for short RS codes.

A personal history of the Viterbi algorithm

Abstract: This paper describes how Andrew J. Viterbi developed a non-sequential decoding algorithm which proved useful in showing the superiority of convolutional codes over block codes for a given degree of decoding complexity. The Viterbi algorithm is now used in most digital cellular phones and digital satellite receivers as well as in such diverse fields as magnetic recoding, voice recognition, and DNA sequence analysis.

LDPC convolutional codes using layered decoding algorithm for high speed coherent optical transmission

Abstract: We successfully realized layered decoding for LDPC convolutional codes designed for application in high speed optical transmission systems. A relatively short code with 20% redundancy was FPGA-emulated with a Q-factor of 5.7dB at BER of 10−15.