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IEEE Communications Letters

Efficient Stopping Criterion for Hybrid Weighted Symbol-Flipping Decoding of Nonbinary LDPC Codes

Bing Liu, Gaoqi Dou, Wei Tao, Jun Gao

Published Jan 24, 2011• 6 citations
Publisher

Abstract

A two-stage hybrid iterative decoding algorithm with an efficient stopping criterion for nonbinary low-density parity-check (LDPC) codes is proposed, which combines weighted symbol-flipping (WSF) algorithm and fast Fourier transform q-ary sum-product algorithm (FFT-QSPA). The first WSF decoding would be stopped in advance by analyzing the trend of the number of unsatisfied checks. If the first stage decoding is stopped or failed, the second powerful FFT-QSPA is activated. The proposed decoding with the efficient stopping achieves error performance as good as that of FFT-QSPA with a low complexity, and converges faster than hybrid WSF (HWSF) algorithm.

DOI
10.1109/lcomm.2011.011811.102348

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A two-stage hybrid iterative decoding algorithm with an efficient stopping criterion for nonbinary low-density parity-check (LDPC) codes is proposed, which combines weighted symbol-flipping (WSF) algorithm and fast Fourier transform q-ary sum-product algorithm (FFT-QSPA). The first WSF decoding would be stopped in advance by analyzing the trend of the number of unsatisfied checks. If the first stage decoding is stopped or failed, the second powerful FFT-QSPA is activated. The proposed decoding with the efficient stopping achieves error performance as good as that of FFT-QSPA with a low complexity, and converges faster than hybrid WSF (HWSF) algorithm.
A hybrid decoding algorithm which proposed for nonbinary and binary low density parity (LDPC) codes, both the algorithm combines the weighted symbol flipping (WSF) algorithm with the fast Fourier transform q-ary sum product algorithm (FFT-QSPA).The flipped position and value are determined by the symbol flipping metric and the received bit values in the first stage WSF algorithm. If the low complexity WSF algorithm is failed, the second stage FFT-QSPA is activated as a switching strategy. They are particularly effective for decoding LDPC codes constructed based on finite geometries and finite fields. Analyzing both the techniques nonbinary LDPC codes gives the better error performance and greatly reduces the computation complexity compared to binary LDPC codes. The proposed hybrid algorithm is used for some applications in communication systems for high speed and low power consumption. Keywords Nonbinary and binary low density parity-check (LDPC) code, Weighted symbol –flipping (WSF), Hybrid weighted symbol-flipping (HWSF), iterative decoding. 1.
In this paper, a new low-complexity symbol-flipping algorithm to decode nonbinary low-density parity-check (LDPC) codes is proposed. The decoding procedure updates iteratively the hard-decision received symbol vector in search of a valid codeword in the symbol vector space. Only one symbol is changed in each iteration, and symbol flipping function combines the number of failed checks and reliability of the received bits and calculated symbols. An optional mechanism to avoid infinite loops in high Galois field search is also proposed. Our studies show that the algorithm achieves an appealing tradeoff between performance and complexity over relatively low Galois field for short to medium code length.
To speed up the convergence rate of non-binary low-density parity check codes and reduce decoding computational complexity of decoding algorithm, a weighted symbol flipping decoding algorithm based on iterative stopping criteria is proposed. The algorithm determines the position and amplitude of the flipped symbol according to the weight of the information node and the flipping function in the check equation, and selects the optimal value of the weighting factor through simulation. At the same time, the iteration stop criterion is introduced, and the iteration is stopped by setting the number of parity equations without satisfying the different signal-to-noise ratio. The simulation results show that the channel additive white Gauss noise, the algorithm ensures the invariant properties of weighted symbol flipping decoding algorithm under the condition that can accelerate the convergence speed, reduce the average number of iterations, so the decoding performance and complexity trad-off between effective.
A properly designed stopping criterion for iterative decoding algorithms can save a number of iterations and lead to a considerable reduction of system latency. The symbol flipping decoding algorithms based on prediction (SFDP) have been proposed recently for efficient decoding of non-binary low-density parity-check (LDPC) codes. To detect the decoding frames with slow convergence or even non-convergence, we track the number of oscillations on the value of objective function during the iterations. Based on this tracking number, we design a simple stopping criterion for the SFDP algorithms. Simulation results show that the proposed stopping criterion can significantly reduce the number of iterations at low signal-to-noise ratio regions with slight error performance degradation.
This paper analyzes a weighted symbol-flipping (SF) algorithm for nonbinary low density parity-check (NB-LDPC) codes over binary input AWGN (BI-AWGN) channels. The weighted SF algorithm has two main parts: the symbol-flipping function and the new candidate symbol rule. First, it is demonstrated that a rule for choosing the new candidate symbol based on absolute values of observed channel outputs is equivalent to a rule based on Euclidean distances. Then, it is verified that the weighting factor of flipping function has negligible impact on algorithm performance. Motivated by this fact, a SF decoding algorithm is proposed whose flipping function requires only syndrome values and flips symbols in parallel. It is observed that SF decoding outperforms WSF for q-ary codes with large q.
A new low-complexity symbol-flipping algorithm based on majority decision to decode nonbinary low-density parity-check (LDPC) codes is proposed. The decoding procedure updates iteratively the hard-decision received symbol vector in search of a valid codeword in the symbol vector space. Only one symbol is changed in each iteration, and symbol flipping function combines the number of failed checks and reliability of the received bits and calculated symbols. Flipped symbol position is determined by majority decision and flipped value is calculated by channel output. And an optional mechanism to avoid infinite loops in high Galois field search is also proposed. Our studies show that the algorithm achieves an appealing tradeoff between performance and complexity over relatively low Galois field for short to medium code length.