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IEEE Vehicular Technology Conference

Modified Iterative Two-Stage Hybrid Decoding Algorithm for Low-Density Parity-Check (LDPC) Codes

Hany R. Zeidan, Maha Mohamed Elsabrouty

Published Apr 1, 2009• 8 citations
Publisher

Abstract

This paper considers a modified iterative version of the two-stage hybrid algorithm for decoding low-density parity- check (LDPC) codes. The hybrid-decision scheme is a decoding scheme used that combines two iterative decoding algorithms for decoding LDPC codes. This scheme is suitable for many applications such as audio and video transmission that are sensitive to time. The hybrid-decision scheme mixes between the characteristics of the soft-decision decoding scheme and the hard- decision decoding scheme to reduce the computational complexity of the whole decoding algorithm. The modification proposed in this paper is applied to the implementation-efficient reliability ratio weighted bit-flipping (IERRWBF) algorithm which represents hard-decision scheme in the hybrid algorithm. This modification is capable of achieving better performance than that of the hybrid decoding algorithm with reducing the number of iterations required at each SNR and approaching more to the performance of the SPA. This reduction is more observable as the maximum number of iterations assigned for the algorithm increases or as the code length increases with improving the error performance as proved by simulation results.

DOI
10.1109/vetecs.2009.5073688

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•Jan 1, 2007•0 citations
This paper considers a modified iterative version of the two-stage hybrid algorithm for decoding low-density parity- check (LDPC) codes. The hybrid-decision scheme is a decoding scheme used that combines two iterative decoding algorithms for decoding LDPC codes. This scheme is suitable for many applications such as audio and video transmission that are sensitive to time. The hybrid-decision scheme mixes between the characteristics of the soft-decision decoding scheme and the hard- decision decoding scheme to reduce the computational complexity of the whole decoding algorithm. The modification proposed in this paper is applied to the implementation-efficient reliability ratio weighted bit-flipping (IERRWBF) algorithm which represents hard-decision scheme in the hybrid algorithm. This modification is capable of achieving better performance than that of the hybrid decoding algorithm with reducing the number of iterations required at each SNR and approaching more to the performance of the SPA. This reduction is more observable as the maximum number of iterations assigned for the algorithm increases or as the code length increases with improving the error performance as proved by simulation results.
The reliability ratio weighted based bit-flipping (RRWBF) algorithm for decoding low-density parity-check (LDPC) codes has recently been developed to provide the best performance among all existing bit-flipping based algorithms. The implementation efficient reliability ratio weighted based bit-flipping (IERRWBF) algorithm speedup the original algorithm to decrease the processing time used. A drawback for this algorithm is the decrease in the improvement as the maximum number of iterations assigned for the algorithm increase as a large percentage of decoding time is spent on the iteration part without any change in the performance. In this paper, a modified version for this algorithm is proposed to solve this drawback by reducing the number of iterations required to achieve the same performance of the existing IERRWBF algorithm using efficient number of iterations instead of using the maximum number of iterations for decoding without any change in the performance of the IERRWBF.
Soft decision decoders applicable to low density parity check codes such as sum product algorithms provide excellent error performance, however, it comes at the expense of computational complexity. Additionally, many iterations may be required of these decoders to achieve desired error performance. The processing delay associated with too many iterations may be a drawback for cases where low latency is a critical requirement. Conversely, performance of hard decision decoders such as bit flipping decoder and its variants, while improved, generally are not on par with that of soft decision decoders. Such decoders also require many iterations to achieve a given error performance. We have proposed a two-stage hybrid decoder with a simplified sum product algorithm (SPA) in the first stage, and an improved noisy gradient decent bit flipping decoder in the second stage. We have shown that our proposed hybrid decoder outperforms the legacy individual decoders, studied in this paper, from error performance point of view as well as required number of iterations that will reduce the overall network latency.
Low-density parity check (LDPC) codes are gaining increased attention in information theory field. However one of the main problems facing usage of these codes in communication systems is its high complexity decoding scheme that results in high decoding delay. Such a delay is not acceptable in many applications. This paper presents, a new hybrid decoding scheme. The proposed scheme mixes between soft-decision and hard-decision algorithms and provides a good tradeoff between error performance and decoding delay as proved by simulation results.
In this paper, a new two-stage hybrid algorithm for decoding Low-Density Parity-Check (LDPC) codes is proposed that incorporates two iterative decoding. For the first stage of decoding, we offer a new decoding algorithm called Improved Variable Multi Weighted Bit-Flipping (IVMWBF) algorithm. Since the IVMWBF algorithm is based on the idea of flipping variable multi bits in each iteration, both improvement in performance and reduction in iteration number and computational complexity are observed in this algorithm. The proposed hybrid algorithm which is a combination of the IVMWBF and BP algorithms, while having a performance exactly similar to that of the BP algorithm, has less complexity compared to that algorithm.
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.
Recent advances in coding theory have uncovered the previously forgotten power of Low-Density Parity-Check (LDPC) codes. Their popularity can be related to their relatively simple iterative decoders and their potential to achieve high performance close to shannon limit. These make them an attractive candidate for error correcting application in communication systems. In this thesis, we focus our research on the iterative decoding algorithms for Low-Density Parity-Check codes and present an improved decoding algorithm. First, the graph structure of LDPC codes is studied and a graph-based search algorithm to find the shortest closed walk and shortest cycle for each node of the graph is proposed. Then, the Deterministic schedule is applied on nodes of the graph with the objective of preserving the optimality of the algorithms. Finally, Hybrid Switch-Type technique is applied on the improved algorithms to provide a desirable complexity/performance trade-off. Hybrid Technique and Deterministic schedule are combined for decoding regular and irregular LDPC codes. The performance and complexity of the decoder is studied for Sum-Product and Gallager A algorithms. The result is a flexible decoder for any available LDPC code and any combination of decoding algorithms based on the communication systems need. In this technique, we benefit the high performance of soft-decision algorithms and low complexity of hard-decision algorithms by changing the decoding rule after a few iterations. Hence, a desirable performance can be obtained with less average number of soft iterations. Moreover, all the nodes do not update messages in each iteration. As a result, the total number of computations is reduced considerably