基于HMM的信源—信道迭代联合译码

提出一种在接收端利用Turbo译码软输出,结合HMM（隐马尔可夫模型）中的Baum-Welch重估算法获取信源模型参数并进行信源-信道迭代联合译码的算法.通过含噪接收序列信道译码后的软输出对信源模型参数进行估计,并将迭代估计获得的信源精确概率结构和信道译码结合进行信源-信道联合迭代译码.同时从信息论角度提出用鉴别信息来度量估计获得的信源模型参数的精度,以及确定迭代估计终止的条件.     

类卷积译码的容错解扰算法

针对自同步扰码系统的联合信源信道译码问题,本文将自同步扰码看作一种特殊的卷积编码,提出了类似卷积译码的软输入软输出(SISO)自同步去扰算法。该算法利用信源冗余更新扰码序列的外信息,在信道译码时作为先验信息进行译码,实现了自同步去扰与信道译码之间的软信息交互,充分利用了信源冗余信息,使得接收系统的性能得到了有效提升。仿真结果表明,在TPC编码条件下,当信源冗余度为70%时,联合信源信道译码的性能增益约为4.1dB。相比于单一纠错编码系统,当通信系统中存在自同步扰码时,联合信源信道译码具有更大的性能增益。      

信源反馈条件下Raptor码的一种解码算法

在Raptor码普通译码方法的基础上,结合信源信道联合译码方法,提出一种利用信源解码器反馈信息作为输入的改进译码的算法,并对此算法进行试验仿真以及参数研究。测试结果显示,在信源信道联合编码条件下,使用这种双信息来源的译码的算法,可以使得信道解码的成功率大幅提高,残留误码率大幅降低。最后,将这种算法与JPEG2000信源编码结合测试,图像的PSNR值比普通译码方法最高提高了6dB。在信道条件恶劣的无线传输中具有重要意义。     

基于MRF的高性能二进制LDPC码译码算法

二进制LDPC码译码改进算法主要是提升硬判决性能或者降低软判决计算复杂度。本文应用高斯-马尔可夫随机场(Markov Random Field,MRF)模型实现信源参数估计,对信道译码端接收的比特序列进行对数似然比修正,在译码时加入信源的残留冗余信息来增加译码器的纠错能力。信源估计修正系数自适应可变,是由误码率参数调控。在计算复杂度不变的情况下,基于MRF的LDPC码译码算法有效提高了译码性能,降低误比特率     

基于隐马尔科夫模型的多元LDPC联合译码

采用隐马尔科夫模型对信源估计,对基于多进制LDPC码的联合信源信道译码算法展开研究。该算法通过对传统的多进制LDPC译码算法的改进,在迭代过程中加入通过估计算法得到的信源冗余,校正了迭代软信息,提高译码性能。仿真结果表明,在AWGN信道中,改进算法相比传统译码算法性能优越。     

迭代结构的信源信道联合解码及其简化算法

信源信道联合解码算法中的迭代信道解码需要进行比特似然值和概率值转换,以及联乘、累加运算,增加了信道解码的计算复杂度,该文针对这一问题,直接利用信道解码的比特硬判决值和参数的先验概率,估计比特的外信息,用于迭代信道解码。基于高斯-马尔可夫信源参数的仿真实验表明,该简化算法大大降低了迭代信道解码算法的计算复杂度。与独立解码算法相比,简化的联合解码算法明显改善了接收参数的信噪比,同时不会明显降低原迭代结构解码算法的性能。     

结合残留冗余信息与MMSE估计的信源信道联合编解码

文中提出一种利用残留冗余的RDPCM信源信道联合编码系统与最小均方误差估计结合的方法.首先,本文针对联合编码系统修正了SOVA算法,在接收端获得利用残留冗余后的比特似然度;然后利用这些后验信息,对信源预测编码器的输出符号值进行最小均方误差重建后再进行信源译码,从而减小了由于硬判决得到符号值所带来的失真.仿真结果显示这种算法在信噪比的低端最大得到了约2dB的增益.     

小波编码图像联合信源信道解码算法的研究

为提高图像在噪声信道中传输的可靠性,该文提出了一种图像联合信源信道解码方案。信源图像首先经离散小波变换,压缩编码。编码数据经RCPC(率兼容删余卷积码)信道编码保护,通过噪声信道传输。在接收端的改进的APRI-SOVA (先验信息软输出维特比算法)在信道解码时,不仅利用了信道输出的软判决,而且进一步利用了信源解码器提供的当前解码的比特的可靠性信息。仿真结果显示,有效利用信源数据中遗留的相关性,能够实现图像解码质量的提高。     

一种利用信源冗余的Turbo均衡新算法

为克服无线衰落信道中严重的符号间干扰( ISI)的影响,提出了一种新的利用信源冗余的Turbo均衡算法。该算法将联合信源信道译码技术与Turbo均衡技术结合起来,在均衡、译码、信源之间建立起软信息交互的环路,有效提高了整体接收的性能。外信息传递( EXIT)图分析与计算机仿真均表明,尽管信源冗余给译码器带来的性能提升较为有限,但是将这部分信息反馈回均衡器后,在严重ISI信道,信源冗余度为70%时,整体接收的性能改善约为9.5 dB,基本达到了理想加性高斯白噪声( AWGN)信道下的误码性能。     

一种利用信源冗余的Turbo均衡新算法

为克服无线衰落信道中严重的符号间干扰(ISI)的影响,提出了一种新的利用信源冗余的Turbo均衡算法。该算法将联合信源信道译码技术与Turbo均衡技术结合起来,在均衡、译码、信源之间建立起软信息交互的环路,有效提高了整体接收的性能。外信息传递(EXIT)图分析与计算机仿真均表明,尽管信源冗余给译码器带来的性能提升较为有限,但是将这部分信息反馈回均衡器后,在严重ISI信道,信源冗余度为70%时,整体接收的性能改善约为9.5 dB,基本达到了理想加性高斯白噪声（AWGN）信道下的误码性能。     

Joint source-channel turbo decoding of entropy-coded sources

We analyze the dependencies between the variables involved in the source and channel coding chain. This analysis is carried out in the framework of Bayesian networks, which provide both an intuitive representation for the global model of the coding chain and a way of deriving joint (soft) decoding algorithms. Three sources of dependencies are involved in the chain: (1) the source model, a Markov chain of symbols; (2) the source coder model, based on a variable length code (VLC), for example a Huffman code; and (3) the channel coder, based on a convolutional error correcting code. Joint decoding relying on the hidden Markov model (HMM) of the global coding chain is intractable, except in trivial cases. We advocate instead an iterative procedure inspired from serial turbo codes, in which the three models of the coding chain are used alternately. This idea of using separately each factor of a big product model inside an iterative procedure usually requires the presence of an interleaver between successive components. We show that only one interleaver is necessary here, placed between the source coder and the channel coder. The decoding scheme we propose can be viewed as a turbo algorithm using alternately the intersymbol correlation due to the Markov source and the redundancy introduced by the channel code. The intermediary element, the source coder model, is used as a translator of soft information from the bit clock to the symbol clock     

SCMA场景下的极化码编解码方案改进研究

极化码是目前唯一一种被证明可达到信道容量的编码方式,稀疏码分多址接入(Sparse Code Division Multiple Access,SCMA)可以提高频谱资源的利用率和接入系统的用户接入数量。为了提升SCMA与极化码的联合系统的误码率性能和译码时延,使联合系统的应用越来越广泛,提出了2种降低译码复杂度的方式:简化的左信息更新方式和剪枝译码算法。简化的左信息更新方式对于N=256,N=1024的极化码分别能降低37.6%和44.6%的存储资源占用数;剪枝译码算法在码率为0.5时能降低50%左右的计算复杂度。基于简化的SCAN算法改进了联合检测译码算法,在接收机采用外循环迭代的结构,引入了阻尼机制,选取最优的阻尼方式和最优阻尼值。仿真分析了所提联合检测译码算法与原有联合检测译码算法的误码率性能差异,外迭代接收机性能与内外双循环迭代的接收机性能相同,采用阻尼机制联合接收机的性能比无阻尼接收机的性能高0.8 dB左右,SJIDD的误帧率性能比保留宽度为32的SCLJDD的性能低0.7 dB左右,但能使接收机处理时延降至原来的1/4~1/8。     

Optimal use of Markov models for DPCM picture transmission over noisy channels

Joint source/channel decoders that use the residual redundancy in the source are investigated for differential pulse code modulation (DPCM) picture transmission over a binary symmetric channel. Markov sequence decoders employing the Viterbi algorithm that use first-order source statistics are reviewed, and generalized for decoders that use second-order source statistics. To make optimal use of the source correlation in both horizontal and vertical directions, it is necessary to generalize the conventional Viterbi decoding algorithm for a one higher-dimensional trellis. The paths through the trellis become two-dimensional "sheets", thus, the technique is coined "sheet decoding". By objective [reconstruction signal-to-noise ratio (SNR)] and subjective measure, it is found that the sheet decoders outperform the Markov sequence decoders that use a first-order Markov model, and outperform two other known decoders (modified maximum a posteriori probability and maximal SNR) that use a second-order Markov model. Moreover, it is found that the use of a simple rate-2/3 block code in conjunction with Markov model-aided decoding (MMAD) offers significant performance improvement for a 2-bit DPCM system. For the example Lenna image, it is observed that the rate-2/3 block code is superior to a rate-2/3 convolutional code for channel-error rates higher than 0.035. The block code is easily incorporated into any of the MMAD DPCM systems and results in a 2-bit MMAD DPCM system that significantly outperforms the noncoded 3-bit MMAD DPCM systems for channel-error rates higher than 0.04.     

基于纠错算术码的信源信道自适应联合编解码系统

对信源信道自适应联合编码方法进行了研究,提出了一种新的基于纠错算术码的联合信源信道编解码系统。该系统在编码端利用算术码内嵌禁用符号实现信源信道一体式编码,即利用马尔科夫信源模型和根据信道状态信息自适应地调整禁用符号概率大小从而调整编码码率来实现信道自适应;在解码端,推导出了基于MAP的解码测度数学公式并基于此测度公式提出了一种改进的堆栈序列估计算法。与传统的信道自适应编码算法不同,该自适应编码算法只需调整一个参数:禁用符号,且理论上可获得连续可变的编码码率。实验结果表明,与经典的Grangetto联合编码系统以及分离编码系统相比,所提出的编码系统具有明显改善的性能增益。     

Hybrid symbol- and bit-based source-controlled channel decoding for MELP speech parameters

A joint source channel coding (JSCC) scheme which exploits bit-level correlation as well as symbol-level correlation efficiently in a source-controlled channel decoding (SCCD) process is proposed and applied to the mixed-excitation linear prediction (MELP) parameters of speech. A modified BCJR algorithm is also proposed for use in the SCCD algorithm. Simulation results show that our proposed scheme performs better than other redundancy-based JSCC schemes such as bit-based SCCD, soft-bit speech decoding (SBSD) and iterative source-channel decoding.     

Iterative Source-Channel Decoding With Markov Random Field Source Models

We propose a joint source-channel decoding approach for multidimensional correlated source signals. A Markov random field (MRF) source model is used which exemplarily considers the residual spatial correlations in an image signal after source encoding. Furthermore, the MRF parameters are selected via an analysis based on extrinsic information transfer charts. Due to the link between MRFs and the Gibbs distribution, the resulting soft-input soft-output (SISO) source decoder can be implemented with very low complexity. We prove that the inclusion of a high-rate block code after the quantization stage allows the MRF-based decoder to yield the maximum average extrinsic information. When channel codes are used for additional error protection the MRF-based SISO source decoder can be used as the outer constituent decoder in an iterative source-channel decoding scheme. Considering an example of a simple image transmission system we show that iterative decoding can be successfully employed for recovering the image data, especially when the channel is heavily corrupted.     

An integrated error correction and detection system for digitalaudio broadcasting

Hybrid in-band on-channel digital audio broadcasting systems deliver digital audio signals in such a way that is backward compatible with existing analog FM transmission. We present a channel error correction and detection system that is well-suited for use with audio source coders, such as the so-called perceptual audio coder (PAC), that have error concealment/mitigation capabilities. Such error mitigation is quite beneficial for high quality audio signals. The proposed system involves an outer cyclic redundancy check (CRC) code that is concatenated with an inner convolutional code. The outer CRC code is used for error detection, providing flags to trigger the error mitigation routines of the audio decoder. The inner convolutional code consists of so-called complementary punctured-pair convolutional codes, which are specifically tailored to combat the unique adjacent channel interference characteristics of the FM band. We introduce a novel decoding method based on the so-called list Viterbi algorithm (LVA). This LVA-based decoding method, which may be viewed as a type of joint or integrated error correction and detection, exploits the concatenated structure of the channel code to provide enhanced decoding performance relative to decoding methods based on the conventional Viterbi algorithm (VA). We also present results of informal listening tests and other simulations on the Gaussian channel. These results include the preferred length of the outer CRC code for 96-kb/s audio coding and demonstrate that LVA-based decoding can significantly reduce the error flag rate relative to conventional VA-based decoding, resulting in dramatically improved decoded audio quality. Finally, we propose a number of methods for screening undetected errors in the audio domain