LDPC(Low Density Parity Check)码是无线通信系统中高效的信道编码技术,并已经在第五代移动通信等系统中应用,码率兼容则是在应用中遇到的重要问题之一。码率兼容的关键在于在不增加译码复杂度的情况下,实现低码率到高码率的任意变化...LDPC(Low Density Parity Check)码是无线通信系统中高效的信道编码技术,并已经在第五代移动通信等系统中应用,码率兼容则是在应用中遇到的重要问题之一。码率兼容的关键在于在不增加译码复杂度的情况下,实现低码率到高码率的任意变化。论文提出了一种码率兼容多元LDPC码的比特级打孔算法。该算法首先将多元符号矩阵转换为二元比特矩阵,其次利用最小环路检测算法检测每个比特变量节点所在环路大小,并选择大环路比特变量节点进行打孔。仿真结果表明,针对码长256、码率0.5的非规则四元LDPC码及码长155、码率0.4得规则LDPC码,论文所提算法均大约有0.1dB~0.25 dB的增益。展开更多
This paper is concerned with design-ing symbol labeling for a low-density parity-check(LDPC)-coded delayed bit-interleaved coded modu-lation(DBICM)scheme in a two-way relay channel(TWRC).We first present some properti...This paper is concerned with design-ing symbol labeling for a low-density parity-check(LDPC)-coded delayed bit-interleaved coded modu-lation(DBICM)scheme in a two-way relay channel(TWRC).We first present some properties of symbol labeling within a phase shift keying(PSK)modula-tion.These properties reduce the candidate labeling search space.Based on this search space,we take DBICM capacity as the cost function and propose a general method for optimizing symbol labeling by em-ploying the differential evolution algorithm.Numeri-cal results show that our labeling obtains a signal-to-noise ratio(SNR)gain up to 0.45 dB with respect to Gray labeling.展开更多
文摘LDPC(Low Density Parity Check)码是无线通信系统中高效的信道编码技术,并已经在第五代移动通信等系统中应用,码率兼容则是在应用中遇到的重要问题之一。码率兼容的关键在于在不增加译码复杂度的情况下,实现低码率到高码率的任意变化。论文提出了一种码率兼容多元LDPC码的比特级打孔算法。该算法首先将多元符号矩阵转换为二元比特矩阵,其次利用最小环路检测算法检测每个比特变量节点所在环路大小,并选择大环路比特变量节点进行打孔。仿真结果表明,针对码长256、码率0.5的非规则四元LDPC码及码长155、码率0.4得规则LDPC码,论文所提算法均大约有0.1dB~0.25 dB的增益。
文摘This paper is concerned with design-ing symbol labeling for a low-density parity-check(LDPC)-coded delayed bit-interleaved coded modu-lation(DBICM)scheme in a two-way relay channel(TWRC).We first present some properties of symbol labeling within a phase shift keying(PSK)modula-tion.These properties reduce the candidate labeling search space.Based on this search space,we take DBICM capacity as the cost function and propose a general method for optimizing symbol labeling by em-ploying the differential evolution algorithm.Numeri-cal results show that our labeling obtains a signal-to-noise ratio(SNR)gain up to 0.45 dB with respect to Gray labeling.
