利用变量节点符号可靠度在迭代过程中的分布特征,提出了一种基于可靠度差值特征的自适应判决多元低密度奇偶校验(Low Density Parity Check, LDPC)译码算法。整个迭代过程划分为两个阶段,针对不同阶段节点可靠度的差值特征分别采用不同...利用变量节点符号可靠度在迭代过程中的分布特征,提出了一种基于可靠度差值特征的自适应判决多元低密度奇偶校验(Low Density Parity Check, LDPC)译码算法。整个迭代过程划分为两个阶段,针对不同阶段节点可靠度的差值特征分别采用不同的判决策略:前期阶段,采用传统的基于最大可靠度的判决策略;后期阶段,根据最大、次大可靠度之间的差值特征,设计自适应的码元符号判决策略。仿真结果表明,所提算法在相当的译码复杂度前提下,能获得0.15~0.4 dB的性能增益。同时,对于列重较小的LDPC码,具有更低的译码错误平层。展开更多
低密度奇偶校验(Low-Density Parity-Check,LDPC)码是第五代移动通信技术(5th Generation Mobile Communication Technology,5G)系统采用的信道编码技术之一,用于业务信道高速数据传输,具有很强的抗干扰能力和纠错能力。5G-LDPC码编译...低密度奇偶校验(Low-Density Parity-Check,LDPC)码是第五代移动通信技术(5th Generation Mobile Communication Technology,5G)系统采用的信道编码技术之一,用于业务信道高速数据传输,具有很强的抗干扰能力和纠错能力。5G-LDPC码编译码在嵌入式平台的实现是一个值得关注的研究方向。CEVA-XC4500数字信号处理(Digital Signal Processing,DSP)芯片具有极低功耗、高密度计算、集成了超长指令字(Very Long Instruction Word,VLIW)和单指令多数据(Single Instruction Multiple Data,SIMD)矢量功能的特点。针对CEVA-XC4500 DSP矢量汇编指令和内联指令集的特点,提出一系列针对5G-LDPC码编码的代码优化方法,使其满足5G-LDPC码编码工程应用指标要求。仿真结果表明,优化后的5G-LDPC码编码在CEVA-XC4500 DSP内核上表现良好,中长块编码吞吐率超过100 Mb/s、核心矩阵吞吐率超过1 Gb/s,最大吞吐率达到250 Mb/s、最大核心矩阵吞吐率达到1.6 Gb/s。如果CEVA-XC4500 DSP芯片的最大数据位宽将来能进一步增大,吞吐率可以做得更好。该5G-LDPC码编码的代码优化方法为其他信道编码在类似嵌入式平台的实现提供了参考。展开更多
In this paper, both the high-complexity near-ML list decoding and the low-complexity belief propagation decoding are tested for some well-known regular and irregular LDPC codes. The complexity and performance trade-of...In this paper, both the high-complexity near-ML list decoding and the low-complexity belief propagation decoding are tested for some well-known regular and irregular LDPC codes. The complexity and performance trade-off is shown clearly and demonstrated with the paradigm of hybrid decoding. For regular LDPC code, the SNR-threshold performance and error-floor performance could be improved to the optimal level of ML decoding if the decoding complexity is progressively increased, usually corresponding to the near-ML decoding with progressively increased size of list. For irregular LDPC code, the SNR-threshold performance and error-floor performance could only be improved to a bottle-neck even with unlimited decoding complexity. However, with the technique of CRC-aided hybrid decoding, the ML performance could be greatly improved and approached with reasonable complexity thanks to the improved code-weight distribution from the concatenation of CRC and irregular LDPC code. Finally, CRC-aided 5GNR-LDPC code is evaluated and the capacity-approaching capability is shown.展开更多
文摘In this paper, both the high-complexity near-ML list decoding and the low-complexity belief propagation decoding are tested for some well-known regular and irregular LDPC codes. The complexity and performance trade-off is shown clearly and demonstrated with the paradigm of hybrid decoding. For regular LDPC code, the SNR-threshold performance and error-floor performance could be improved to the optimal level of ML decoding if the decoding complexity is progressively increased, usually corresponding to the near-ML decoding with progressively increased size of list. For irregular LDPC code, the SNR-threshold performance and error-floor performance could only be improved to a bottle-neck even with unlimited decoding complexity. However, with the technique of CRC-aided hybrid decoding, the ML performance could be greatly improved and approached with reasonable complexity thanks to the improved code-weight distribution from the concatenation of CRC and irregular LDPC code. Finally, CRC-aided 5GNR-LDPC code is evaluated and the capacity-approaching capability is shown.
