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。      

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。     

Turbo decodulation: iterative combined demodulation and source-channel decoding

We propose the combination of iterative demodulation and iterative source-channel decoding as a multiple turbo process. The receiver structures of bit-interleaved coded modulation with iterative decoding (BICM-ID), iterative source-channel decoding (ISCD), and iterative source coded modulation (ISCM) are merged to one novel turbo system, in which in two iterative loops reliability information is exchanged between the three single components, demodulator, channel decoder and (softbit) source decoder. Simulations show quality improvements compared to the different previously known systems, which use iterative processing only for two components of the receiver.     

Low-complexity iterative joint source-channel decoding for variable-length encoded Markov sources

In this paper, we present a novel packetized bit-level decoding algorithm for variable-length encoded Markov sources, which calculates reliability information for the decoded bits in the form of a posteriori probabilities (APPs). An interesting feature of the proposed approach is that symbol-based source statistics in the form of the transition probabilities of the Markov source are exploited as a priori information on a bit-level trellis. This method is especially well-suited for long input blocks, since in contrast to other symbol-based APP decoding approaches, the number of trellis states does not depend on the packet length. When additionally the variable-length encoded source data is protected by channel codes, an iterative source-channel decoding scheme can be obtained in the same way as for serially concatenated codes. Furthermore, based on an analysis of the iterative decoder via extrinsic information transfer charts, it can be shown that by using reversible variable-length codes with a free distance of two, in combination with rate-1 channel codes and residual source redundancy, a reliable transmission is possible even for highly corrupted channels. This justifies a new source-channel encoding technique where explicit redundancy for error protection is only added in the source encoder.     

Joint turbo decoding and estimation of hidden Markov sources

We describe a joint source-channel scheme for modifying a turbo decoder in order to exploit the statistical characteristics of hidden Markov sources. The basic idea is to treat the trellis describing the hidden Markov source as another constituent decoder which exchanges information with the other constituent decoder blocks. The source block uses as extrinsic information the probability of the input bits that is provided by the constituent decoder blocks. On the other hand, it produces a new estimation of such a probability which will be used as extrinsic information by the constituent turbo decoders. The proposed joint source-channel decoding technique leads to significantly improved performance relative to systems in which source statistics are not exploited and avoids the need to perform any explicit source coding prior to transmission. Lack of a priori knowledge of the source parameters does not degrade the performance of the system, since these parameters can be jointly estimated with turbo decoding     

LDPC-based iterative joint source-channel decoding for JPEG2000.

A framework is proposed for iterative joint source-channel decoding of JPEG2000 codestreams. At the encoder, JPEG2000 is used to perform source coding with certain error-resilience (ER) modes, and LDPC codes are used to perform channel coding. During decoding, the source decoder uses the ER modes to identify corrupt sections of the codestream and provides this information to the channel decoder. Decoding is carried out jointly in an iterative fashion. Experimental results indicate that the proposed method requires fewer iterations and improves overall system performance.     

Doubly Iterative Equalization of Continuous-Phase Modulation

In this paper, a doubly iterative receiver is proposed for joint turbo equalization, demodulation, and decoding of coded binary continuous-phase modulation (CPM) in multipath fading channels. The proposed receiver consists of three soft-input soft-output (SISO) blocks: a front-end soft-information-aided minimum mean square error (MMSE) equalizer followed by a CPM demodulator and a back-end channel decoder. The MMSE equalizer, combined with an a priori soft-interference canceler (SIC) and an a posteriori probability mapper, forms a SISO processor suitable for iterative processing that considers discrete-time CPM symbols which belong to a finite alphabet. The SISO CPM demodulator and the SISO channel decoder are both implemented by the a posteriori probability algorithm. The proposed doubly iterative receiver has a central demodulator coupled with both the front-end equalizer and the back-end channel decoder. A few back-end demodulation/decoding iterations are performed for each equalization iteration so as to improve the a priori information for the equalizer. As presented in the extrinsic information transfer (EXIT) chart analysis and simulation results for different multipath fading channels, this provides not only faster convergence to low bit error rates, but also lower computational complexity.     

Iterative joint source-channel decoding of variable-length codes using residual source redundancy

We present a novel symbol-based soft-input a posteriori probability (APP) decoder for packetized variable-length encoded source indexes transmitted over wireless channels where the residual redundancy after source encoding is exploited for error protection. In combination with a mean-square or maximum APP estimation of the reconstructed source data, the whole decoding process is close to optimal. Furthermore, solutions for the proposed APP decoder with reduced complexity are discussed and compared to the near-optimal solution. When, in addition, channel codes are employed for protecting the variable-length encoded data, an iterative source-channel decoder can be obtained in the same way as for serially concatenated codes, where the proposed APP source decoder then represents one of the two constituent decoders. The simulation results show that this iterative decoding technique leads to substantial error protection for variable-length encoded correlated source signals, especially, when they are transmitted over highly corrupted channels.     

A generalized framework for iterative source-channel decoding

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.     

Analysis and optimization of irregular LDPC codes for joint source-channel decoding

In this paper, we present a characterization, through its convergence analysis, and an optimisation of a joint source-channel receiver composed of a LDPC decoder and a Soft Input Soft Output (SISO) source decoder. Under Gaussian approximation, assuming the knowledge of the extrinsic mutual information transfer function (EXIT chart) of the source decoder, we derive the Mutual Information evolution equations, that semianalytically describe the convergence of the iterative system behavior and, to complete the study, the stability condition at the convergence fixed point is derived for the joint receiver. From this analysis, a general optimisation method of the irregularity of the LDPC codes is proposed, which can be reduced to a linear programming optimisation problem. Simulation results show improved performance when compared to an AWGN optimized LDPC code.     

Correction of extrinsic information for iterative decoding in a serially concatenated multiuser DS-CDMA system

The system under study is a coded asynchronous DS-CDMA system with orthogonal modulation in time-varying Rayleigh fading multipath channels. Information bits are convolutionally encoded, block interleaved, and mapped to M-ary orthogonal Walsh codes, where the last step is essentially a process of block coding. This paper aims at tackling the problem of joint iterative decoding of this serially concatenated inner block code and outer convolutional code and estimating frequency-selective fading channels in multiuser environments. The (logarithm) maximum a posteriori probability, (Log)-MAP criterion is used to derive the iterative decoding schemes. In our system, the soft output from inner block decoder is used as a priori information for the outer decoder. The soft output from outer convolutional decoder is used for two purposes. First, it may be fed back to the inner decoder as extrinsic information for the systematic bits of the Walsh codeword. Secondly, it is utilized for channel estimation and multiuser detection (MUD). We also show that the inner decoding can be accomplished without extrinsic information, and in some cases, e.g., when the system is heavily loaded, yields better performance than the decoding with unprocessed extrinsic information. This implies the need for correcting the extrinsic information obtained from outer decoder. Different schemes are examined and compared numerically, and it is shown that iterative decoding with properly corrected extrinsic information or with non-extrinsic/extrinsic adaptation enables the system to operate reliably in the presence of severe multiuser interference, especially when the inner decoding is assisted by decision directed channel estimation and interference cancellation techniques.     

Soft multiuser decoding for vector quantization over a CDMA channel

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     

"Turbo DPSK" using soft multiple-symbol differential sphere decoding

Coded interleaved differential M-ary phase-shift keying (M-DPSK) with iterative decoding, the so-called "Turbo DPSK," is known as a power-efficient transmission format. Due to the rotational invariance of DPSK, it particularly enables detection without channel state information (CSI). However, the soft-input soft-output (SISO) component decoder for DPSK is the computational bottleneck if performance close to the ideal case of perfect CSI is desired. In this paper, we take a fresh look at SISO decoding without CSI and apply sphere decoding (SD) to reduce complexity. In particular, we devise a maximum a posteriori probability (MAP) multiple-symbol differential sphere decoder (MSDSD) which efficiently solves the high-dimensional search problem inherent to detection without CSI. Together with a soft-output generation device the MAP-MSDSD algorithm forms a new SISO-MSDSD module for iterative decoding. We analyze the extrinsic information transfer (EXIT) characteristic of the novel module, by means of which we are able to design powerful encoder and decoder structures. For, respectively, the additive white Gaussian noise (AWGN) and the continuously time-varying Rayleigh-fading channel without CSI these designs operate within 1.7-1.9 and 2.3-2.5 dB of channel capacity assuming perfect CSI. These figures compare favorably with results available in the literature, especially for reasonably high data rates of 1-2 bit/channel use. Simulation studies of the average and the maximum complexity required by SISO-MSDSD demonstrate the advantageous performance versus complexity tradeoff of our approach.     

基于不同外信息处理方式的Turbo迭代译码研究

针对离散无记忆高斯信道,该文深入剖析了不同外信息使用方式下的两种对数域的Turbo码迭代译码算法,并借助蒙特卡罗仿真,在相同的约束条件下对两种算法的性能进行了比较。经过分析指出二者在本质上是一致的,只是成员译码器对外信息使用权重的处理不同。最后对其进行了统一的描述,并定量研究了迭代译码对外信息的依赖性。结果发现成员译码器对外信息的最佳依赖程度不受信噪比与迭代次数的影响。     

Iterative (turbo) soft interference cancellation and decoding forcoded CDMA

The presence of both multiple-access interference (MAI) and intersymbol interference (ISI) constitutes a major impediment to reliable communications in multipath code-division multiple-access (CDMA) channels. In this paper, an iterative receiver structure is proposed for decoding multiuser information data in a convolutionally coded asynchronous multipath DS-CDMA system. The receiver performs two successive soft-output decisions, achieved by a soft-input soft-output (SISO) multiuser detector and a bank of single-user SISO channel decoders, through an iterative process. At each iteration, extrinsic information is extracted from detection and decoding stages and is then used as a priori information in the next iteration, just as in turbo decoding. Given the multipath CDMA channel model, a direct implementation of a sliding-window SISO multiuser detector has a prohibitive computational complexity. A low-complexity SISO multiuser detector is developed based on a novel nonlinear interference suppression technique, which makes use of both soft interference cancellation and instantaneous linear minimum mean-square error filtering. The properties of such a nonlinear interference suppressor are examined, and an efficient recursive implementation is derived. Simulation results demonstrate that the proposed low complexity iterative receiver structure for interference suppression and decoding offers significant performance gain over the traditional noniterative receiver structure. Moreover, at high signal-to-noise ratio, the detrimental effects of MAI and ISI in the channel can almost be completely overcome by iterative processing, and single-user performance can be approached     

Design of fixed-point iterative decoders for concatenated codeswith interleavers

We discuss the effects of quantization on the performance of the iterative decoding algorithm of concatenated codes with interleavers. Quantization refers here to the log-likelihood ratios coming from the soft demodulator and to the extrinsic information passed from one stage of the decoder to the next. We discuss the cases of a single soft-input soft-output (SISO) module, in its additive log-likelihood version (L-SISO), performing sequentially all iterations (an implementation solution coping with medium-low data rate as compared with the hardware clock), and that of a pipelined structure in which a dedicated hardware is in charge of each SISO operation (an implementation suitable for high data rates). We give design rules in both cases, and show that a suitable rescaling of the extrinsic information yields almost ideal performance with the same number of bits (five) representing both log-likelihood ratios and extrinsic information at any decoder stage     

Turbo codes for image transmission-a joint channel and sourcedecoding approach

This paper studies an application of turbo codes to compressed image/video transmission and presents an approach to improving error control performance through joint channel and source decoding (JCSD). The proposed approach to JCSD includes error-free source information feedback, error-detected source information feedback, and the use of channel soft values (CSV) for source signal postprocessing. These feedback schemes are based on a modification of the extrinsic information passed between the constituent maximum a posteriori probability (MAP) decoders in a turbo decoder. The modification is made according to the source information obtained from the source signal processor. The CSVs are considered as reliability information on the hard decisions and are further used for error recovery in the reconstructed signals. Applications of this joint decoding technique to different visual source coding schemes, such as spatial vector quantization, JPEG coding, and MPEG coding, are examined. Experimental results show that up to 0.6 dB of channel SNR reduction can be achieved by the joint decoder without increasing computational cost for various channel coding rates     

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。     

Near-Shannon/Slepian-Wolf performance for unknown correlated sources over AWGN channels

We consider the problem of joint source-channel coding of two correlated binary information sequences. Instead of compressing the information using source coding, both sequences are independently channel encoded and transmitted over two independent additive white Gaussian noise channels. No information about the correlation between the sources is required in the encoding process. The correlation between both sequences is exploited at the receiver, allowing reliable communications at signal-to-noise ratios very close to the theoretical limits established by the combination of Shannon and Slepian-Wolf theorems. This occurs even when the correlation between sources is not known at the decoder, since it can be estimated jointly with the iterative decoding process.     

Iterative joint source-channel decoding with combined a priori information of source and channel

A joint source-channel decoding (JSCD) scheme which exploits the combined a priori information of source and channel in an iterative manner is proposed. A sequence minimum mean-square error (SMMSE) estimator based on bit or symbol error transition probability of the channel with memory is proposed and used in the iterative decoding process. Simulation results show that our proposed scheme leads to significant improvement over the scheme without using the a priori information of the source or channel.