幅度与相位联合调制(Amplitude and Phase Shift Keying,APSK)对于映射到星座图上同一个符号点的不同比特具有不均等的差错保护,其中受保护程度较低的比特限制了编码调制系统的整体误码性能。为消除这一限制,提出了一种非均衡编码方案,...幅度与相位联合调制(Amplitude and Phase Shift Keying,APSK)对于映射到星座图上同一个符号点的不同比特具有不均等的差错保护,其中受保护程度较低的比特限制了编码调制系统的整体误码性能。为消除这一限制,提出了一种非均衡编码方案,即对不同保护程度的数据进行分组,通过比特交织的方式匹配不同纠错能力的低密度奇偶校验码(Low Density Parity Check Code,LDPC)进行编码。在64-APSK调制方式下进行计算机仿真,仿真结果表明:均衡编码方案相比传统编码调制方案具有0.3 dB以上的性能增益。展开更多
Non-uniform quantization for messages in Low-Density Parity-Check(LDPC)decoding canreduce implementation complexity and mitigate performance loss.But the distribution of messagesvaries in the iterative decoding.This l...Non-uniform quantization for messages in Low-Density Parity-Check(LDPC)decoding canreduce implementation complexity and mitigate performance loss.But the distribution of messagesvaries in the iterative decoding.This letter proposes a variable non-uniform quantized Belief Propaga-tion(BP)algorithm.The BP decoding is analyzed by density evolution with Gaussian approximation.Since the probability density of messages can be well approximated by Gaussian distribution,by theunbiased estimation of variance,the distribution of messages can be tracked during the iteration.Thusthe non-uniform quantization scheme can be optimized to minimize the distortion.Simulation resultsshow that the variable non-uniform quantization scheme can achieve better error rate performance andfaster decoding convergence than the conventional non-uniform quantization and uniform quantizationschemes.展开更多
文摘幅度与相位联合调制(Amplitude and Phase Shift Keying,APSK)对于映射到星座图上同一个符号点的不同比特具有不均等的差错保护,其中受保护程度较低的比特限制了编码调制系统的整体误码性能。为消除这一限制,提出了一种非均衡编码方案,即对不同保护程度的数据进行分组,通过比特交织的方式匹配不同纠错能力的低密度奇偶校验码(Low Density Parity Check Code,LDPC)进行编码。在64-APSK调制方式下进行计算机仿真,仿真结果表明:均衡编码方案相比传统编码调制方案具有0.3 dB以上的性能增益。
基金the Aerospace Technology Support Foun-dation of China(No.J04-2005040).
文摘Non-uniform quantization for messages in Low-Density Parity-Check(LDPC)decoding canreduce implementation complexity and mitigate performance loss.But the distribution of messagesvaries in the iterative decoding.This letter proposes a variable non-uniform quantized Belief Propaga-tion(BP)algorithm.The BP decoding is analyzed by density evolution with Gaussian approximation.Since the probability density of messages can be well approximated by Gaussian distribution,by theunbiased estimation of variance,the distribution of messages can be tracked during the iteration.Thusthe non-uniform quantization scheme can be optimized to minimize the distortion.Simulation resultsshow that the variable non-uniform quantization scheme can achieve better error rate performance andfaster decoding convergence than the conventional non-uniform quantization and uniform quantizationschemes.
