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Journal of Spacecraft TT&C Technology

A Soft-Input Soft-Output Decoding Algorithm for LDPC Codes

Lixin Wang

Published Jan 1, 2011• 0 citations
OpenAlex

Abstract

A new soft-input,soft-output algorithm for decoding LDPC codes is described in this paper.Using soft squared Euclidean distance as the metric,the algorithm realizes decoding by iterating the antilog-sum of the Euclidean distance.A simplified algorithm is also put forward to reduce computational complexity.The proposed algorithm does not require knowledge of the signal-to-noise ratio of the received signal and is less complex to implement than other soft decision algorithms.The results of simulation show that the performance is very close to that of sum-product algorithm while the computational complexity is sharply reduced.

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•Jul 10, 1996•7 citations
A new soft-input,soft-output algorithm for decoding LDPC codes is described in this paper.Using soft squared Euclidean distance as the metric,the algorithm realizes decoding by iterating the antilog-sum of the Euclidean distance.A simplified algorithm is also put forward to reduce computational complexity.The proposed algorithm does not require knowledge of the signal-to-noise ratio of the received signal and is less complex to implement than other soft decision algorithms.The results of simulation show that the performance is very close to that of sum-product algorithm while the computational complexity is sharply reduced.
To deal with the complexity of traditional BP decoding algorithm,a kind of blind decoding algorithm for LDPC codes based on soft-input,soft-output is put forward in this paper.The algorithm uses soft squared Euclidean distance as the metric,realizes decoding by iterating the antilog-sum of the Euclidean distance as the process taken in BP algorithm.The proposed algorithm does not require knowledge of the signal-to-noise ratio of the received signal,and is less complex to implement than other soft decision algorithms.At the same time,a simplified algorithm is also put forward to reduce the computational complexity.What's more,the proposed SBSD decoding algorithm can not only decode Binary LDPC codes,but also can be used for Qary-LDPC codes.Simulations results show that the proposed algorithm can achieve good performance not only on the AWGN channels but also on Rayleigh channel,and the performance is very close to that of the sum-product algorithm,but the computational complexity is reduced sharply.
Low-density parity-check (LDPC) codes are very efficient error control codes that are being considered for use in many next-generation communication systems. In this study low complexity soft-input, soft-output (SISO) field programmable gate arrays (FPGA) implementations of a novel logarithmic sum-product (LogSP) iterative LDPC decoder and a recently proposed simplified soft Euclidean distance (SSD) iterative LDPC decoder are presented, and their complexities and performance are compared. These implementations operate over any choice of parity check matrix (including those randomly generated, structurally generated and either systematic or non-systematic) and can be parametrically adapted for any code rate. The proposed implementations are both of very low complexity, because they operate using only sums, subtractions, comparisons and look-up tables, which makes them particularly suitable for FPGA realisation. The SSD decoder has a lower implementation complexity than the LogSP LDPC decoder and it also offers the advantage of not requiring knowledge of the channel signal-to-noise ratio, unlike most other LDPC decoders.
A high-performance low-complexity decoding algorithm for LDPC codes is proposed in this paper, which has the advantages of both bit-flipping (BF) algorithm and sum-product algorithm (SPA). The proposed soft bit-flipping algorithm requires only simple comparison and addition operations for computing the messages between bit and check nodes, and the amount of those operations is also small. By increasing the utilization ratio of the computed messages and by adopting nonuniform quantization, the signal-to-noise ratio (SNR) gap to the SPA is reduced to 0.4dB at the frame error rate of 10-4 with only 5-bit assignment for quantization. LDPC codes with high column or row weights, which are not suitable for the SPA decoding due to the complexity, can be practically implemented without much worsening the error performance.