For quantum sparse graph codes with stabilizer formalism, the unavoidable girth-four cycles in their Tanner graphs greatly degrade the iterative decoding performance with standard belief-propagation （BP） algorithm. ...For quantum sparse graph codes with stabilizer formalism, the unavoidable girth-four cycles in their Tanner graphs greatly degrade the iterative decoding performance with standard belief-propagation （BP） algorithm. In this paper, we present a jointly-check iterative algorithm suitable for decoding quantum sparse graph codes efficiently. Numerical simulations show that this modified method outperforms standard BP algorithm with an obvious performance improvement.展开更多
In this paper,a family of rate-compatible(RC) low-density parity-check(LDPC) convolutional codes can be obtained from RC-LDPC block codes by graph extension method.The resulted RC-LDPC convolutional codes,which are de...In this paper,a family of rate-compatible(RC) low-density parity-check(LDPC) convolutional codes can be obtained from RC-LDPC block codes by graph extension method.The resulted RC-LDPC convolutional codes,which are derived by permuting the matrices of the corresponding RC-LDPC block codes,are systematic and have maximum encoding memory.Simulation results show that the proposed RC-LDPC convolutional codes with belief propagation(BP) decoding collectively offer a steady improvement on performance compared with the block counterparts over the binary-input additive white Gaussian noise channels(BI-AWGNCs).展开更多
信道编码参数的盲识别作为非合作通信和自适应调制编码(Adaptive Modulation and Coding,AMC)系统中的一项重要技术,近些年受到了更多关注.在第五代移动通信技术(5th Generation mobile networks,5G)中,其采用了低密度奇偶检验(Low-Dens...信道编码参数的盲识别作为非合作通信和自适应调制编码(Adaptive Modulation and Coding,AMC)系统中的一项重要技术,近些年受到了更多关注.在第五代移动通信技术(5th Generation mobile networks,5G)中,其采用了低密度奇偶检验(Low-Density Parity-Check,LDPC)码作为数据信道的前向纠错码,但其使用了删余和填充导致传统的盲识别技术不再适用.本文提出了一种新的方案,借鉴置信传播(Belief Propagation,BP)译码迭代思路来进行盲识别.该方案基于传统平均对数似然比(Log-Likelihood Ratio,LLR)算法,进一步采用BP译码的思想对删余和填充比特进行迭代,以解决传统算法无法识别这部分比特的问题.仿真结果表明:与现有的相关算法相比,本文算法具有更好的性能.展开更多
基金Project supported by the National Natural Science Foundation of China(Grant No.60972046)Grant from the National Defense Pre-Research Foundation of China
文摘For quantum sparse graph codes with stabilizer formalism, the unavoidable girth-four cycles in their Tanner graphs greatly degrade the iterative decoding performance with standard belief-propagation （BP） algorithm. In this paper, we present a jointly-check iterative algorithm suitable for decoding quantum sparse graph codes efficiently. Numerical simulations show that this modified method outperforms standard BP algorithm with an obvious performance improvement.
基金the National Natural Science Foundation of China(Nos.61401164,61471131 and 61201145)the Natural Science Foundation of Guangdong Province(No.2014A030310308)
文摘In this paper,a family of rate-compatible(RC) low-density parity-check(LDPC) convolutional codes can be obtained from RC-LDPC block codes by graph extension method.The resulted RC-LDPC convolutional codes,which are derived by permuting the matrices of the corresponding RC-LDPC block codes,are systematic and have maximum encoding memory.Simulation results show that the proposed RC-LDPC convolutional codes with belief propagation(BP) decoding collectively offer a steady improvement on performance compared with the block counterparts over the binary-input additive white Gaussian noise channels(BI-AWGNCs).
文摘信道编码参数的盲识别作为非合作通信和自适应调制编码(Adaptive Modulation and Coding,AMC)系统中的一项重要技术,近些年受到了更多关注.在第五代移动通信技术(5th Generation mobile networks,5G)中,其采用了低密度奇偶检验(Low-Density Parity-Check,LDPC)码作为数据信道的前向纠错码,但其使用了删余和填充导致传统的盲识别技术不再适用.本文提出了一种新的方案,借鉴置信传播(Belief Propagation,BP)译码迭代思路来进行盲识别.该方案基于传统平均对数似然比(Log-Likelihood Ratio,LLR)算法,进一步采用BP译码的思想对删余和填充比特进行迭代,以解决传统算法无法识别这部分比特的问题.仿真结果表明:与现有的相关算法相比,本文算法具有更好的性能.
