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IEEE International Conference on Communication Technology (ICCT)

Performance and processing time enhancement of LDPC decoder using stopping node modified Sum Product algorithm

Nguyen Thi Dieu Linh, Gang Wang, Abdelhafidh Barkana, Georgia Rugumira

Published Sep 1, 2011• 2 citations
Publisher

Abstract

In this paper, a new method based on Sum Product algorithm (SPA) using stopping node to reduce computing complexity on Low Density Parity Check Codes (LDPC) decoding algorithms is presented. We show how to make early decisions to reduce calculation of the next iteration. Simulation results show that performance of iterative decoding for LDPC codes using stopping node algorithm can reduce up to 10 times computational complexity with maintaining quality level.

DOI
10.1109/icct.2011.6157845

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In this paper, a new method based on Sum Product algorithm (SPA) using stopping node to reduce computing complexity on Low Density Parity Check Codes (LDPC) decoding algorithms is presented. We show how to make early decisions to reduce calculation of the next iteration. Simulation results show that performance of iterative decoding for LDPC codes using stopping node algorithm can reduce up to 10 times computational complexity with maintaining quality level.
Low-Density-Parity-Check Code (LDPC) codes have received great attention recently because of the excellent error-correcting capability and optional error correct code. A new method base on Min-Sum-Plus-Correction-Factor Algorithm using stopping node to reduce computing complexity on Low-Density-Parity-Check Code decoding algorithm is presented in this paper. The improved method shows how to make early decisions to reduce computation complexity of LDPC decoding algorithm in the next iteration under QPSK systems. Simulation results show that computational complexity of LDPC decoding using Stopping node criterion can reduce up to 6 times with maintaining quality level.
Among the decoding algorithms for low-density parity-check(LDPC) code,sum-product algorithm(SPA) has the optimal performance but high complexity,while min-sum algorithm has simple implementation complexity but worse performance.Considering this performance-complexity contradiction,some modified min-sum algorithms are proposed.In this paper,researches are done based on one of the modified min-sum algorithms that is close to SPA in performance but the way modifying fraction works is simplified.Simplified algorithm remains similar in performance to sum-product algorithm but has a remarkably reduced implementation complexity.
In this paper, an improved low-complexity sum-product decoding algorithm is presented for low-density parity-check (LDPC) codes. In the proposed algorithm, reduction in computational complexity is achieved by utilizing fast Fourier transform (FFT) with time shift in the check node process. The improvement in the decoding performance is achieved by utilizing an optimized integer constant in the variable node process. Simulation results show that the proposed algorithm achieves an overall coding gain improvement ranging from 0.04 to 0.46 dB. Moreover, when compared with the sum-product algorithm (SPA), the proposed decoding algorithm can achieve a reduction of 42%–67% of the total number of arithmetic operations required for the decoding process.
This letter proposes a new algorithm for the check node update in the decoding of low-density parity-check (LDPC) codes. The proposed algorithm is based on a new approximation formula of standard sum-product algorithm (SPA) which can reduce the approximation error of min-sum algorithm (MSA) and has almost the same performance as sum-product algorithm (SPA) under both floating precision operation and fixed-point operation. Besides, the new approximation formula can be implemented in simple structures competitive with MSA.
We present in this paper a new method for improving the decoding of the LDPC (low-density parity check) codes by optimising the log-SPA (sum-product algorithm). Currently, the LDPC codes give very good results with iterative decoding algorithm, log-SPA, based on the propagation confidence BP (belief propagation). To improve the existing log-SPA, we propose a decoding algorithm (log-SPA modified), which minimises the error decoding of words that could not be previously decoded. This algorithm is based on the dependency between the weight of the syndrome and the weight of the error sequence generated during iterations of decoding. Simulations illustrate the performance of our approach compared with classical LDPC code based on log-SPA.