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Generalized simplified variable-scaled min sum LDPC decoder for irregular LDPC codes

机译:用于不规则LDPC码的广义简化可变比例最小和LDPC解码器

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In this paper, we propose a novel low complexity scaling strategy of min-sum decoding algorithm for irregular LDPC codes. In the proposed method, we generalize our previously proposed simplified Variable Scaled Min-Sum (SVS-min-sum) by replacing the sub-optimal starting value and heuristic update for the scaling factor sequence by optimized values. Density evolution and Nelder-Mead optimization are used offline, prior to the decoding, to obtain the optimal starting point and per iteration updating step size for the scaling factor sequence of the proposed scaling strategy. The optimization of these parameters proves to be of noticeable positive impact on the decoding performance. We used different DVB-T2 LDPC codes in our simulation. Simulation results show the superior performance (in both WER and latency) of the proposed algorithm to other Min-Sum based algorithms. In addition to that, generalized SVS-min-sum algorithm has very close performance to LLR-SPA with much lower complexity.
机译:在本文中,我们提出了一种新的低复杂度缩放算法,用于不规则LDPC码的最小和解码算法。在提出的方法中,我们通过用优化值代替次优起始值和对比例因子序列的启发式更新,来概括先前提出的简化的可变比例最小和(SVS-min-sum)。在解码之前,离线使用密度演化和Nelder-Mead优化来获得最佳起点,并针对所建议缩放策略的缩放因子序列,每次迭代更新步长。这些参数的优化被证明对解码性能具有明显的积极影响。我们在仿真中使用了不同的DVB-T2 LDPC码。仿真结果表明,与其他基于最小和的算法相比,该算法具有更高的性能(在WER和延迟方面)。除此之外,广义的SVS-min-sum算法与LLR-SPA具有非常接近的性能,且复杂度低得多。

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