International Conference on Wireless Communications and Signal Processing (WCSP)

Hybrid iterative decoding for LDPC codes based on gradient descent bit-flipping algorithm

Hua Li, Hong Wei Ding, Linhua Zheng

Published Oct 1, 2016• 0 citations

Abstract

Gradient descent bit-flipping (GDBF) decoding for low-density parity-check (LDPC) codes has gained great attentions because of low complexity and relatively good performance. However, the performance of the GDBF decoding is still much poorer than that of the MS algorithm. To further improve the performance, the iterative decoding process is introduced to GDBF decoding in this paper. At the end of each iteration, the latest information is used to update the reliability of the flipped bit, by which its reliability is greatly improved. Simulation results indicate that the proposed algorithm has about 0.4 dB performance gains compared to GDBF. Meanwhile, there is small computational complexity increased.

DOI: 10.1109/wcsp.2016.7752445

Related papers

Efficient Bit-Flipping Decoding Algorithm for Structured LDPC Codes

Cheng He, Yuzhu Wang

The Gradient descent bit flipping (GDBF) algorithm is a representative approach for decoding low-density parity-check (LDPC) codes, which offers a good tradeoff between decoding performance and complexity. Unfortunately, the decoding performance of GDBF algorithm degenerates dramatically for structured LDPC codes due to their large column weight. To address the above issue, we propose to improve GDBF algorithm by introducing a weighted parameter in the energy function of each bit. Specifically, this parameter compensates for the computational error of the energy function due to the large column weight of the parity-check matrices of structured LDPC codes. Moreover, the flipping number of each bit in the iterative process is included in the energy function to avoid consecutive bit flips in the decoding. Simulation results on typical structured LDPC codes indicate that the performance of the proposed algorithm is better than the standard GDBF algorithm at the cost of slight increment in the algorithmic complexity. The increase operations can be easily implemented, which indicates the proposed algorithm is suitable for practical purposes.

International Conference on Neural Networks, Information and Communication Engineering (NNICE)Jan 10, 20250 citations

An improved noisy gradient descent bit-flipping decoding algorithm for LDPC codes

Jun Asatani, Yuya Kondo, Kengo Katayama +2 more

Gradient descent bit-flipping (GDBF) algorithm achieves good error performance for decoding low density parity check codes. In the GDBF algorithm, a search point is apt to be trapped in a local optimum, which causes performance degradation of the GDBF algorithm. To overcome this issue, the noisy GDBF algorithm introduces random perturbation into the inversion function of each symbol, which decreases the probability of being trapped in a local optimum. In this paper, we develop the noisy GDBF algorithm by enhancing the threshold adaptation in multi-bit flipping procedure to improve the BER performance without increasing the time complexity.

International Symposium on Information Theory and its ApplicationsOct 1, 20162 citations

A modified gradient descent bit flipping decoding scheme for LDPC codes

Mao-Ruei Li, Li-Min Jhuang, Yeong-Luh Ueng

It is known that the Gradient descent bit flipping (GDBF) algorithm is an effective hard-decision decoding algorithm for low-density parity-check (LDPC) codes. However, trapping in a local maximum limits its error-rate performance. This paper presents a modified GDBF scheme that can mitigate the trapping problem and hence can improve the error-rate performance. Compared to the conventional GDBF algorithm, the proposed method is able to improve the decoding performance of 0.3dB for an (18582, 16626) code. The (18582, 16626) LDPC decoder integrates 636k logic gates and achieves a throughput of 12.4 Gbps at a clock frequency of 200 MHz in a 90nm process.

SiPS ... design and implementation - IEEE Workshop on Signal Processing SystemsOct 1, 20174 citations

Noisy Gradient Descent Bit-Flip Decoding for LDPC Codes

Gopalakrishnan Sundararajan, Chris Winstead, Emmanuel Boutillon

A modified Gradient Descent Bit Flipping (GDBF) algorithm is proposed for decoding Low Density Parity Check (LDPC) codes on the binary-input additive white Gaussian noise channel. The new algorithm, called Noisy GDBF (NGDBF), introduces a random perturbation into each symbol metric at each iteration. The noise perturbation allows the algorithm to escape from undesirable local maxima, resulting in improved performance. A combination of heuristic improvements to the algorithm are proposed and evaluated. When the proposed heuristics are applied, NGDBF performs better than any previously reported GDBF variant, and comes within 0.5 dB of the belief propagation algorithm for several tested codes. Unlike other previous GDBF algorithms that provide an escape from local maxima, the proposed algorithm uses only local, fully parallelizable operations and does not require computing a global objective function or a sort over symbol metrics, making it highly efficient in comparison. The proposed NGDBF algorithm requires channel state information which must be obtained from a signal to noise ratio (SNR) estimator. Architectural details are presented for implementing the NGDBF algorithm. Complexity analysis and optimizations are also discussed.

arXiv:1402.2773IEEE Transactions on CommunicationsSep 9, 2014108 citations

Syndrome-Aided Gradient Descent Bit Flipping Algorithm for LDPC Decoding

Yuang Huang, Haiyang Liu

Gradient descent bit flipping (GDBF) algorithm is an important low-complexity method for decoding LDPC codes. In particular, the multi-bit GDBF decoding has the best decoding performance among BF algorithms if a suitable threshold is prescribed. However, extensive computer searches are needed to find such a threshold for a specific LDPC code. In this paper, we propose a syndrome-aided GDBF (SAGDBF) algorithm to address the problem. The thresholds in our algorithm are adaptively adjusted according to the syndrome values in the iterative process. Simulation results for different LDPC codes suggest that the error performances of the proposed SAGDBF algorithm are close to and even better than the original multi-bit GDBF algorithm at a relatively small number of iterations. In addition, the complexity increased in our proposed algorithm is negligible compared with the original multi-bit GDBF algorithm. Hence, the proposed algorithm is suitable for practical purposes.

IEEE International Conference on Computer and Communications (ICCC)Dec 11, 20202 citations

Gradient-Descent Bit-Flipping Decoding Based on Tabu Search for LDPC Codes

良介高橋, 祐一高野

This paper is concerned with bit-flipping algorithms for decoding low-density parity check codes. The gradient-descent bit flipping (GDBF) is known as a high-performance class of bitflipping algorithms; however, once GDBF becomes trapped at local optimal solutions, it cannot escape from them. Several algorithms, including noisy gradient-descent bit flipping (NGDBF), have been devised to overcome this drawback. For the same purpose, we develop a bit-flipping algorithm based on the tabu search, which is one of the most effective metaheuristics. The simulation results demonstrate that our algorithm achieved higher bit error rate performance than GDBF did. Moreover, our algorithm required a smaller number of iterations to find a good-quality solution than NGDBF did.

Mar 1, 20190 citations