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Video Engineering

Improving LDPC Decoding Algorithm with Informed Dynamic Scheduling

An Q

Published Jan 1, 2014• 0 citations
OpenAlex

Abstract

To reduce the complexity and improve the performance of the decoding algorithm for Low Density Parity Check(LDPC) codes,an improved algorithm NW-RBPF based on the number of the updates of the check-nodes completed in an iteration is presented in this paper,which uses the minBP and a convergence factor to calculate the residual mentioned in NW-RBP algorithm.In this paper,the convergence factor is obtained by calculating the BERs using different factors.Simulations show that the algorithm achieves better performance than the NW-RBP algorithm in 0.05 dB.It also outperforms NW-RBP for a large numbers of iterations.Therefore,this algorithm provides both good performance and convergence speed for any check node degree distribution in the LDPC codes.

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IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)•Sep 1, 2013•4 citations
To reduce the complexity and improve the performance of the decoding algorithm for Low Density Parity Check(LDPC) codes,an improved algorithm NW-RBPF based on the number of the updates of the check-nodes completed in an iteration is presented in this paper,which uses the minBP and a convergence factor to calculate the residual mentioned in NW-RBP algorithm.In this paper,the convergence factor is obtained by calculating the BERs using different factors.Simulations show that the algorithm achieves better performance than the NW-RBP algorithm in 0.05 dB.It also outperforms NW-RBP for a large numbers of iterations.Therefore,this algorithm provides both good performance and convergence speed for any check node degree distribution in the LDPC codes.
We researched BP decoding algorithm based on variable-to-check information residual for LDPC code (VC-RBP) in this paper. It is a dynamic scheduling belief propagation using residuals, and has some advantages, such as fast decoding, good performance, and low complexity. It is similar to residual belief propagation (RBP),but has some difference in computing the residual message. Simulation shows that it outperforms with only a maximum of ten iterations by about 0.28 dB compared with RBP at an BER of 10-4.
In order to improve the error correction performance of Low-Density Parity-Check (LDPC) codes, In this paper, we propose a Reliability Profile (RP) Based Low-Complexity Dynamic Schedule, called RPD. In terms of dynamic scheduling, the new RPD method is distinct from the existing residual belief propagation (RBP) and its variations, since RPD is based on residual criterion. Reliability divides nodes message into two categories: reliable and unreliable. By using as many messages as possible from the latest available current iteration instead of the previous iteration to update unreliable messages multiple times to speed up the convergence speed and increase the total number of updates of effective nodes message, so as to improve the Bit Error Rate (BER) performance. By not updating the reliable message, the number of ineffective nodes message updates is reduced, thereby reducing the decoding complexity. Besides, the more iterations increase, the fewer calculations of these reliable nodes. Moreover, based on reliability profile, RPD has an advantage over RBP for dynamic scheduling in that the former only needs integer operations, while the latter requires float operations. Therefore, the RPD algorithm not only accelerates the convergence speed of LDPC decoding and but also improves the BER performance while reducing the complexity.The analysis and simulation results show that the RPD strategy not only retains the fast-convergence advantage of RBP, but also has a better convergence BER performance compared to that of node-wise residual belief propagation (NW RBP). Furthermore, the simulation results show that the RPD can significantly improve the convergence speed of protograph LDPC decoding.
The informed dynamic scheduling (IDS) strategies for decoding of low-density parity-check codes obtained superior performance in error correction performance and convergence speed. However, there are still two problems existing in the current IDS algorithms. The first is that the current IDS algorithms only preferentially update the selected unreliable messages, but they do not guarantee the updating is performed with reliable information. In this paper, a two-step message selecting strategy is introduced. On the basis of the two reliability metrics and two types of variable node residuals, the residual belief propagation (BP) decoding algorithm, short for TRM-TVRBP, is proposed. With the algorithm, the reliability of the updating-messages can be improved. The second is the greediness problem, prevalently existed in the IDS-like algorithms. The problem arises mainly from the fact that the major computing resources are allocated to or concentrated on some nodes and edges. To overcome the problem, the reliability metric-based RBP algorithm (RM-RBP) is proposed, which can force every variable node to contribute its intrinsic information to the iterative decoding. At the same time, the algorithm can force the related variable nodes to be updated, and make every edge have an equal opportunity of being updated. The simulation results show that both the TRM-TVRBP and the RM-RBP have appealing convergence rate and error-correcting performance compared with the previous IDS decoders over the white Gaussian noise (AWGN) channel.
Low-density parity-check (LDPC) codes offer excellent performance at competitive levels of complexity. Short block length LDPC codes avoid the large processing latency incurred by the large block lengths classically considered for this class of codes, making them a potential candidate for next generation wireless communications systems. In this paper, a novel informed dynamic scheduling (IDS) approach for decoding LDPC codes is developed based on the use of the current message reliabilities and the residuals of the potential updates to select the messages passed in the graph during iterative Sum Product decoding. An alternative measure of the iteration of the IDS schemes is also proposed which highlights the high cost of those algorithms in terms of processing complexity and motivates the development of the proposed approach. The proposed Rel.-RBP decoding algorithm offers very fast convergence at reduced complexity and gains in error rate performance when compared to the previous schemes.
After the publication of the residual belief-propagation (RBP) algorithm, many low-density parity-check (LDPC) decoders using informed dynamic scheduling (IDS) have been investigated. In this paper, we propose the twofold-RBP (T-RBP) decoder that combines two residuals. Using T-RBP, significant improvement can be achieved in both convergence speed and convergence error-rate performance. In addition to T-RBP, the simplified-RBP (S-RBP) decoder is also proposed in order to reduce the complexity. Instead of comparing all the residuals of all edges in the code graph, as with previous IDS decoders, S-RBP only compares the residuals of the edges connected to a single check node, thus dramatically reduces the complexity without any significant degradation in performance. The proposed T-RBP and S-RBP can improve not only the performance of dedicated codes, but also that of punctured codes, especially the convergence speed. The improvement can make punctured LDPC codes more practical and becoming a competitive candidate for the rate compatible applications.