Canadian Workshop on Information Theory (CWIT)

On the correlation between error weights and syndrome weights for belief propagation decoding of LDPC codes

Irina Adjudeanu, Jean‐Yves Chouinard, Paul Fortier

Published May 1, 2009• 7 citations

Abstract

This paper analyzes the correlation between the error weights and the syndrome weights during the sum product algorithm (SPA) decoding process of low density parity check codes (LDPC) in order to improve the error performance and the decoding speed. In this paper, we propose a modified SPA decoding algorithm to improve the decoding performance of the non-decoded codewords and investigate if this new algorithm takes indeed the best decoding decision for each codeword. The effect of the averaged decoding over the error weights and syndrome weights are analyzed as well as their correlation. The correlation coefficients between them are computed and a weight enumerator polynomial is used to jointly represent the error and syndrome weight distribution for each codeword.

DOI: 10.1109/cwit.2009.5069516

Related papers

Optimising LDPC Codes Using Modified Log SPA Algorithm

Abdessadek Aaroud, Mohammed Mensouri

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.

International Journal of Applied Research on Information Technology and ComputingJan 1, 20140 citations

Channel Mismatch Effect on Performance of Low Density Parity Check Codes

Liu Qi, Chen Gong, Huijuan Cui +1 more

Effect of channel mismatch on decoding performance of low density parity check (LDPC) codes over binary symmetric channel (BSC) under sum-product algorithm (SPA) is analyzed in this paper. Density evolution is employed in theoretical analysis to get optimal initial value for SPA. Based on the results, a modified SPA algorithm is proposed. When decoding using this modified SPA algorithm, no channel information is needed at the decoder side. This will be of significant value for time-varying channels. Theoretical claims from density evolution are confirmed by extensive simulations. Our simulations show that by fixing the initial value for all channel conditions, decoding performance can be improved. One channel state estimation algorithm is proposed in this paper based on the error detection ability of LDPC codes. Maximum number of iterations taken when decoding a LDPC code can be dynamically adjusted according to the estimated channel state. Further performance improvements can be achieved by using the dynamic iteration number adjusting scheme together with the modified sum-product algorithm

The Multiconference on Computational Engineering in Systems ApplicationsOct 1, 20060 citations

A hybrid belief propagation decoding algorithms of LDPC codes for fast convergence

Tso-Cho Chen, Chia‐Jung Li, Erl‐Huei Lu

A hybrid belief propagation (BP) decoding algorithm for low-density parity-check code is proposed to accelerate the convergence of decoding and reduce the number of decoding iterations. The hybrid scheme is presented by integrating the BP algorithm with the bit-flipping function which is used as adaptive weighted factor in the BP iteration decoding. The adaptive weighting factor is based on the average weighted reliability measure of the hard output of decoder. The proposed hybrid adaptive weighted iteration scheme can efficiently increase the convergence speed of the belief propagation decoding and therefore improve the error performance. Simulation results show that the proposed algorithm can significantly reduce the decoding complexity and achieve better error performances as compared with the sum-product algorithm.

Cross Strait Radio Science and Wireless Technology Conference (CSRSWTC)Jul 1, 20135 citations

On Combining Chase-2 and Sum-Product Algorithms for LDPC Codes

Sheng Tong

This letter investigates the combination of the Chase-2 and sum-product (SP) algorithms for low-density parity-check (LDPC) codes. A simple modification of the tanh rule for check node update is given, which incorporates test error patterns (TEPs) used in the Chase algorithm into SP decoding of LDPC codes. Moreover, a simple yet effective approach is proposed to construct TEPs for dealing with decoding failures with low-weight syndromes. Simulation results show that the proposed algorithm is effective in improving both the waterfall and error floor performance of LDPC codes.

ETRI JournalJul 30, 20126 citations

Improved LDPC decoding algorithms based on min-sum algorithm

Y.V. A. C. Kumara, Chandika Bandara Wavegedara

Low-Density Parity check (LDPC) codes offer high-performance error correction near the Shannon limit which employs large code lengths and some iterations in the decoding process. The conventional decoding algorithm of LDPC is the Log Likelihood Ratio based Belief Propagation (LLR BP) which is also known as the `Sum-Product algorithm' which gives the best decoding performance and requires the most computational complexity and implementations with increased hardware complexity. Another simpler variant of this algorithm is used which is known as `min-sum algorithm' which reduces computational complexity as well as hardware complexity but with reduced accuracy. This paper analyzes the reason min-sum algorithm is more prone to errors when compared to the sum-product algorithm, and puts forward two improved algorithms which improve the performance of the min-sum algorithm with comparable algorithmic complexity.

Moratuwa Engineering Research Conference (MERCon)Apr 1, 20168 citations

Performance Evaluation of A Modified Sum-Product Decoding Algorithm for LDPC Codes

Stylianos Papaharalabos, P. Sweeney, B.G. Evans +3 more

We propose a modified hyperbolic tangent (tanh) function that is used in the sum-product algorithm (SPA). This is done in order to approximate the infinite argument of the tanh function, when decoding low-density parity-check (LDPC) codes. As shown by computer simulation results, the proposed modification has a significant impact on the error floor reduction of the code and to the coding gain improvement with respect to the SPA with no modification. Computer simulation results with approximations using both piecewise linear function and coarse quantization are also presented

International Symposium on Wireless Communication SystemsDec 10, 200511 citations