针对符号间干扰信道的多天线分集接收问题,提出一种单输入多输出(SIMO)系统盲迭代均衡算法。该算法利用吉布斯样本法处理思路,在SIMO条件下推导了信道冲击响应、发送符号等未知参数的条件后验分布,根据该条件概率逐个参数进行随机采样,...针对符号间干扰信道的多天线分集接收问题,提出一种单输入多输出(SIMO)系统盲迭代均衡算法。该算法利用吉布斯样本法处理思路,在SIMO条件下推导了信道冲击响应、发送符号等未知参数的条件后验分布,根据该条件概率逐个参数进行随机采样,通过不断迭代更新来逼近最大后验概率(MAP)估计的结果。该算法的一个显著特点是具有软输入软输出(SISO)结构,因此在编码系统中可以与信道译码结合,通过联合迭代进一步提升均衡的性能。计算机仿真结果表明,在严重符号间干扰信道条件下,SIMO系统盲迭代均衡算法的性能非常接近于已知信道时迭代均衡算法的性能,距离理想无符号间干扰信道分集合成的性能差距只有约1 d B。展开更多
为提高水声通信系统的数据传输速率和可靠性,提出一种新的基于软信道估计的联合迭代均衡译码(joint iterative equalization and decoding,JIED)水声通信方法。该方法利用软输入软输出(soft in soft out,SISO)译码器反馈的外似然比计算...为提高水声通信系统的数据传输速率和可靠性,提出一种新的基于软信道估计的联合迭代均衡译码(joint iterative equalization and decoding,JIED)水声通信方法。该方法利用软输入软输出(soft in soft out,SISO)译码器反馈的外似然比计算符号软估计信息,并应用于稀疏自适应信道估计器的抽头系数更新过程。经过译码器和均衡器之间多次迭代交换软信息联合处理接收信号,信道估计精度与均衡效果显著提高。水声通信实验结果表明在通信距离1.8km、2kHz有效带宽内,新方法在第2次迭代后即可实现2kb/s的无误码传输,可以有效提高系统可靠性和传输速率。展开更多
In order to fully utilize the soft decision ability of the outer decoder in a concatenated system, reliability information (called soft output) from the inner decoder or equalizer is required. In this paper, based on...In order to fully utilize the soft decision ability of the outer decoder in a concatenated system, reliability information (called soft output) from the inner decoder or equalizer is required. In this paper, based on the analysis of typical implementations of soft output VA, a novel algorithm is proposed by utilizing the property of Viterbi algorithm. Compared with the typical implementations, less processing expense is required by the new algorithm for weighting the hard decisions of VA. Meanwhile, simulation results show that, deterioration in performance of this algorithm is usually small for decoding of convolutional code and negligible for equalization.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
A Jointly Gaussian (JG) equalizer is derived for turbo equalization based on an augmented real matrix representation of channel model and a Gaussian approximation of the received symbol sequence. Using matrix inversio...A Jointly Gaussian (JG) equalizer is derived for turbo equalization based on an augmented real matrix representation of channel model and a Gaussian approximation of the received symbol sequence. Using matrix inversion lemma and Cholesky decomposition, a lowcomplexity implementation of JG equalizer is also presented. The simulation results and complexity comparison confirm that turbo equalization with JG equalizer has a better performance and a lower complexity than the existing turbo equalization with linear minimum mean squared error equalizer.展开更多
文摘针对符号间干扰信道的多天线分集接收问题,提出一种单输入多输出(SIMO)系统盲迭代均衡算法。该算法利用吉布斯样本法处理思路,在SIMO条件下推导了信道冲击响应、发送符号等未知参数的条件后验分布,根据该条件概率逐个参数进行随机采样,通过不断迭代更新来逼近最大后验概率(MAP)估计的结果。该算法的一个显著特点是具有软输入软输出(SISO)结构,因此在编码系统中可以与信道译码结合,通过联合迭代进一步提升均衡的性能。计算机仿真结果表明,在严重符号间干扰信道条件下,SIMO系统盲迭代均衡算法的性能非常接近于已知信道时迭代均衡算法的性能,距离理想无符号间干扰信道分集合成的性能差距只有约1 d B。
文摘为提高水声通信系统的数据传输速率和可靠性,提出一种新的基于软信道估计的联合迭代均衡译码(joint iterative equalization and decoding,JIED)水声通信方法。该方法利用软输入软输出(soft in soft out,SISO)译码器反馈的外似然比计算符号软估计信息,并应用于稀疏自适应信道估计器的抽头系数更新过程。经过译码器和均衡器之间多次迭代交换软信息联合处理接收信号,信道估计精度与均衡效果显著提高。水声通信实验结果表明在通信距离1.8km、2kHz有效带宽内,新方法在第2次迭代后即可实现2kb/s的无误码传输,可以有效提高系统可靠性和传输速率。
文摘In order to fully utilize the soft decision ability of the outer decoder in a concatenated system, reliability information (called soft output) from the inner decoder or equalizer is required. In this paper, based on the analysis of typical implementations of soft output VA, a novel algorithm is proposed by utilizing the property of Viterbi algorithm. Compared with the typical implementations, less processing expense is required by the new algorithm for weighting the hard decisions of VA. Meanwhile, simulation results show that, deterioration in performance of this algorithm is usually small for decoding of convolutional code and negligible for equalization.
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.
文摘A Jointly Gaussian (JG) equalizer is derived for turbo equalization based on an augmented real matrix representation of channel model and a Gaussian approximation of the received symbol sequence. Using matrix inversion lemma and Cholesky decomposition, a lowcomplexity implementation of JG equalizer is also presented. The simulation results and complexity comparison confirm that turbo equalization with JG equalizer has a better performance and a lower complexity than the existing turbo equalization with linear minimum mean squared error equalizer.
