共查询到19条相似文献,搜索用时 93 毫秒
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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。 相似文献
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基于滑窗置信传播算法的联合信源信道编码 总被引:1,自引:1,他引:0
针对联合信源信道编码中信源统计特性和信道噪声参数未知情况下,解码算法性能急剧下降的问题,提出一种基于滑窗置信传播算法(SWBP)的联合信源信道编码,简称滑窗算法.研究采用不规则重复累积(IRA)码来实现基于滑窗置信传播算法的联合信源信道编码,IRA码可以取得与低密度奇偶校验(LDPC)码同样优越的性能,但编码复杂度远远低于LDPC码.在解码端引入滑动窗口,通过实时地估计不断变化的信源统计特性和信道噪声参数,从而提高解码速率.实验结果表明该算法具有接近相关参数已知情况下的理想性能、不依赖于初始参数、复杂度低且易于实现等优点. 相似文献
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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。 相似文献
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基于参数冗余量分配方案和可变参数估计准则的 GSM EFR信源信道联合解码算法 总被引:1,自引:1,他引:0
该文利用GSM EFR(Enhanced Full Rate)语音编码参数的冗余信息,提出了一种新的基于迭代结构和参数估计的联合解码算法框架;针对GSM EFR编码参数由非等概分布和帧间相关性提供的冗余量,本文提出了联合解码算法中两类冗余信息在信道解码,信源解码的分配方案。同时针对不同语音编码参数的特性,引入不同的估计准则。仿真结果表明,该文算法显著提高了GSM EFR参数接收性能,提高了解码语音信噪比,改善了接收系统性能。 相似文献
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由于算法复杂度和延迟的限制,语音编码参数仍然保留了一定的冗余信息,这些冗余量表现为参数的非等概分布和时间相关性。该文在比特级上利用信源编码参数的冗余信息在软输入、软输出信道解码和信源参数估计之间进行迭代运算,并将此联合解码算法运用于GSM EFR系统。仿真结果表明此算法降低了编码参数的BER,提高了解码语音的信噪比,具有一定的可行性和有效性。 相似文献
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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。 相似文献
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在相位和频偏等信道参数未知条件下,Turbo码的解码性能急剧恶化。本文将存在频偏的接收信号等效为高斯白噪声中的正弦信号,提出了一种基于MUSIC算法的信道参数估计算法,并在Turbo码解码中对信道参数进行联合迭代估计。仿真结果表明基于MUSIC算法的Turbo码联合迭代解码的良好性能。 相似文献
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基于HMM的信源—信道迭代联合译码 总被引:2,自引:0,他引:2
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. 相似文献
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Norbert GöRTZ 《电信纪事》2001,56(7-8):435-446
Joint source-channel decoding is considered for a transmission system, in which the quantizer indices of several autocorrelated source signals are bit-interleaved, commonly channel encoded, and transmitted in parallel. Since the optimal decoding algorithm is not feasible in most practical situations, iterative source-channel decoding has been introduced. The latter is generalized in the present paper. Furthermore, it is shown in detail, that iterative source-channel decoding can be derived by insertion of appropriate approximations into the optimal joint decoding algorithm. The approximations allow the decomposition of the optimal decoder into two parts, which can be identified as the constituent decoders for the channel-code and the source-code redundancies. Similar as in other concatenated coding systems, the constituent decoders are applied in an iterative decoding scheme. Its performance is analyzed by simulation results. 相似文献
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We consider joint source-channel and multiuser decoding for frequency selective Rayleigh fading code-division multiple-access channels. The block source-channel encoder is defined by a vector quantizer. We investigate optimal (minimum mean-square error) decoding and “user-separated” decoding of lower complexity. The studied decoders are soft in the sense that they utilize all soft information available at the receiver. Simulations indicate significant performance gains of the introduced decoders compared with a tandem approach that uses maximum-likelihood multiuser detection plus table-lookup decoding 相似文献
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信息论的经典结果表明,信源信道分离编码是渐进最优的。但现代通信系统对时延、带宽等愈发敏感,分离设计对解码具有无限计算能力这一假设难以成立。带宽有限时,相对于信源信道联合编码,分离编码已被证明是次优的。传统的联合信源信道编码需要复杂的编码方案,相较之下,数据驱动的深度学习技术则带来了新的设计思路。适时地对相关研究成果进行总结,有助于进一步明确深度学习方法解决信源信道联合编码问题的方式,为研究新的研究方向提供依据。首先介绍了基于深度学习的信源压缩方案和端对端收发信机模型,随后分析不同信源类型下的两种联合编码设计思路,最后探讨了基于深度学习的信源信道联合编码的潜在问题和未来的工作方向。 相似文献
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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。 相似文献
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Joint source-channel decoding is formulated as an estimation problem. The optimal solution is stated and it is shown that it is not feasible in many practical systems due to its complexity. Therefore, a novel iterative procedure for the approximation of the optimal solution is introduced, which is based on the principle of iterative decoding of turbo codes. New analytical expressions for different types of information in the optimal algorithm are used to derive the iterative approximation. A direct comparison of the performance of the optimal algorithm and its iterative approximation is given for a simple transmission system with “short” channel codewords. Furthermore, the performance of iterative joint source-channel decoding is investigated for a more realistic system 相似文献
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Two common source-channel coding strategies, joint and tandem, are compared on the basis of distortion versus complexity and distortion versus delay by analyzing specific representatives of each when transmitting analog data samples across a binary symmetric channel. Channel-optimized transform coding is the joint source-channel strategy; transform coding plus Reed-Solomon coding is the tandem strategy. For each strategy, formulas for the mean-squared error, computational complexity, and delay are found and used to minimize distortion subject to constraints on complexity and delay, for source data modeled as Gauss-Markov. The results of such optimizations suggest there is a complexity threshold such that when the number of operations per data sample available for encoding and decoding is greater than this threshold, tandem coding is better, and when less, channel-optimized transform coding is better. Similarly, the results suggest there is also a delay threshold such that tandem coding is better than joint coding when the permissible encoding and decoding delay is greater than this threshold. 相似文献
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An approach to optimal soft decoding for vector quantization (VQ) over a code-division multiple-access (CDMA) channel is presented. The decoder of the system is soft in the sense that the unquantized outputs of the matched filters are utilized directly for decoding (no decisions are taken), and optimal according to the minimum mean-squared error (MMSE) criterion. The derived decoder utilizes a priori source information and knowledge of the channel characteristics to combat channel noise and multiuser interference in an optimal fashion. Hadamard transform representations for the user VQs are employed in the derivation and for the implementation of the decoder. The advantages of this approach are emphasized. Suboptimal versions of the optimal decoder are also considered. Simulations show the soft decoders to outperform decoding based on maximum-likelihood (ML) multiuser detection. Furthermore, the suboptimal versions are demonstrated to perform close to the optimal, at a significantly lower complexity in the number of users. The introduced decoders are, moreover, shown to exhibit near-far resistance. Simulations also demonstrate that combined source-channel encoding, with joint source-channel and multiuser decoding, can significantly outperform a tandem source-channel coding scheme employing multiuser detection plus table lookup source decoding 相似文献