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A Novel Fast LDPC Decoder Using APP-based Dynamic Scheduling Scheme

机译:一种新的FAST LDPC解码器,使用基于应用的动态调度方案

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Low-density parity-check (LDPC) codes are favorable in modern telecommunication technologies due to its superior error-correction capability especially when the codeword length is large. The commonly-used LDPC decoders are based on the belief-propagation (BP) algorithms. It is well known that the layered (serial) belief-propagation (LBP) decoding algorithms can reduce the number of iterations by half in comparison with the flooding (parallel) BP decoding algorithms. Further reduction in total number of iterations can be achieved by using the informed dynamic scheduling techniques, such as residual BP (RBP) and node-wise residual BP (NWRBP) methods. However, the incurred additional computation of residuals is far from trivial. In this paper, we propose a novel efficient dynamic scheduling scheme, called a posteriori probability RBP (APPRBP) algorithm, which offers more flexibility to leverage the performance-complexity trade-off using a threshold parameter. The simulation results demonstrate that the average iteration numbers for our proposed APPRBP algorithm can be remarkably reduced especially in the low E_b/N_0 (signal-energy-per-information-bit to noise-power-spectral-density ratio) conditions while the bit-error rate (BER) performance is subject to slight degradation.
机译:低密度奇偶校验(LDPC)码是在现代电信技术有利由于其优越的纠错能力,特别是当码字长度是大的。在通常使用的LDPC解码器是基于置信传播(BP)算法。众所周知的是,分层(串行)置信传播(LBP)的解码算法可以与驱(并行)BP解码算法相比减少一半迭代次数。在迭代的总数目进一步减少可以通过使用所通知的动态调度技术,如残余BP(RBP)和节点明智残余BP(NWRBP)方法来实现。然而,残留物的产生的额外计算还远远没有小事。在本文中,我们提出了一种高效的动态调度方案,称为后验概率RBP(APPRBP)算法,它提供了更大的灵活性,以充分利用性能复杂的权衡使用阈值参数。仿真结果表明,对于我们提出的算法APPRBP平均迭代次数可以特别是在低E_B / N_0(信号能量的每信息位与噪声功率谱密度比)的条件下,而比特被显着地减少误码率(BER)性能是受到轻微降解。

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