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IET International Communication Conference on Wireless Mobile and Computing (CCWMC)

Optimized decoding schedule for irregular LDPC codes

Xuwei Chen, Hui Ling Yu, Youyun Xu

Published Jan 1, 2009• 2 citations
Publisher

Abstract

Recently, the concept of layered decoding schedule for Low-Density Parity-Check codes has been introduced. But the advantage of layered decoding schedule for irregular LDPC codes is not as obvious as regular LDPC codes. The major drawback of the layered irregular LDPC codes versus the layered regular LDPC codes is its comparative low convergence decoding speed. Simulation results show that different bit node degrees of irregular LDPC codes significantly contribute to the decoding performance. The decoding performance of bit nodes with different degrees is of great difference. Bit nodes with small degrees always converge slower than larger ones. In this paper, we propose an optimized decoding schedule for irregular LDPC codes to accelerate the decoding convergence rate. Meanwhile, for the irregular LDPC decoder, the faster decoding speed means a higher throughput and almost the same error performance.

DOI
10.1049/cp.2009.1940

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Recently, the concept of layered decoding schedule for Low-Density Parity-Check codes has been introduced. But the advantage of layered decoding schedule for irregular LDPC codes is not as obvious as regular LDPC codes. The major drawback of the layered irregular LDPC codes versus the layered regular LDPC codes is its comparative low convergence decoding speed. Simulation results show that different bit node degrees of irregular LDPC codes significantly contribute to the decoding performance. The decoding performance of bit nodes with different degrees is of great difference. Bit nodes with small degrees always converge slower than larger ones. In this paper, we propose an optimized decoding schedule for irregular LDPC codes to accelerate the decoding convergence rate. Meanwhile, for the irregular LDPC decoder, the faster decoding speed means a higher throughput and almost the same error performance.
Schedule plays an important role in layered belief propagation (BP) decoding of low-density parity-check (LDPC) codes. It affects the error-rate performance as well as convergence rate of the decoder. In this paper, an efficient scheduling scheme is proposed to arrange the updating order of check nodes for layered BP decoder of regular LDPC codes. This scheme selects check node one at a time based on the reliability of the variable nodes. Specifically each time the check node with maximum number of low-reliability neighbors is selected. For simplicity, we introduce the updating state instead of the real-time messages to represent variable-node reliability. Simulation results on regular LDPC codes prove that the proposed scheduling scheme can obtain efficient schedules with fast convergence and good error-rate performance.
This paper proposes an efficient scheduling algorithm for the layered decoding of block low-density parity-check (LDPC) codes. To efficiently configure check node-based scheduling groups, the proposed algorithm utilizes the base matrix of the block LDPC code for a block-by-block scheduling group configuration; i.e., the proposed algorithm generates a scheduling group of check nodes, satisfying the weight condition of the layered decoding, which is performed in block units (including several check nodes). Therefore, unlike the conventional scheduling algorithms performed in node units, the proposed algorithm can efficiently generate scheduling groups for layered decoding at low computational complexity and memory requirements. In addition, to accelerate the decoding convergence speed, check nodes are allocated in each scheduling group such that messages from check nodes up to the current group are delivered as evenly as possible to bit nodes. Simulation results confirm that the proposed algorithm can accelerate decoding convergence compared to other block-based scheduling algorithms for layered decoding of block LDPC codes.
An efficient dynamic schedule for layered belief-propagation (LBP) decoding of low-density parity-check (LDPC) codes is presented, in which the check nodes connecting to a variable node with maximum relative message residual are chosen in each dynamic decoding iteration, and then LBP is performed for these check nodes. In this schedule we combined the features of lazy schedule and node-wise residual belief propagation (NWRBP) together while keeping the extra computational complexity very low. Simulation results show that the new schedule speeds up the convergence rate and greatly improves error performance at medium to high signal-to-noise ratio (SNR) when compared to the standard LBP decoding algorithm.
In order to reduce the bit error rate of low-density parity-check codes for layered decoding algorithm and improve the decoding convergence speed, an improved layered decoding algorithm is proposed. In layered decoding algorithm, updated bit nodes information can be used by check nodes in the iteration process while in dynamic decoding algorithm check nodes update in order according to the reliability. The proposed algorithm combines advantages of the layered and dynamic decoding algorithm. Moreover, compared with the definition of remaining information for check nodes in the dynamic decoding algorithm, a new method to evaluate the reliability is defined in the proposed algorithm. Based on 1/2 code rate china mobile multimedia broadcasting standard, simulation and comparison between the conventional layered decoding algorithm and the proposed layered decoding algorithm have been carried out. The simulation results show that under the same bit error rate, the signal to noise ratio of the improved algorithm reduces nearly 0.4dB as well as convergence speed improves obviously. The proposed layered decoding algorithm reduces the bit error rate and improves the reliability of data in communication system which uses LDPC codes as the channel coding.
This paper analyzes the performance of quantized min-sum decoding algorithms for irregular low-density parity-check (LDPC) codes. For regular LDPC codes, it is known that the normalized or offset min-sum decoding algorithm with quantization bits less than 6 bits achieves good performances over wide range of signal-to-noise ratios (SNR). However, finite precision effects in decoding irregular LDPC codes are different from that in decoding regular LDPC codes which is caused by the difference of convergence speeds between low degree nodes and high degree nodes. This paper proposes a novel method to improve the performance of the conventional normalized or offset min-sum decoding algorithm when it is approximated with finite precision for hardware implementations. The proposed method applies down-scaling factors to intrinsic information which has effects on increasing the reliability of extrinsic information at variable nodes and compensating the quantization errors caused by finite precision. Computer simulation results for irregular LDPC codes show that the proposed normalized and offset min-sum decoding algorithms achieve better performances at high SNR compared to the conventional normalized and offset min-sum algorithms under (6:2) quantization scheme.