Lossy Distributed Source Coding Using LDPC Codes

In this paper, we propose a practical scheme for lossy distributed source coding with side information available at the decoder. Our proposed scheme is based on sending parity bits using LDPC codes. We provide the design procedure for the LDPC code that guarantees performance close to the Wyner-Ziv limit for long LDPC codes. Using simulation results, we show that the proposed method performs close to the theoretical limit for even short length codes.     

基于边信息改进的分布式信源编码方案

针对现有的非对称分布式信源编码(DSC)方案均存在的在误比特率(BER)以及压缩率方面的不足,该文提出基于边信息改进的DSC(DSCUISI)方案。发送方对信源序列进行抽样,将序列分为抽样与未抽样子序列,利用算术编码器对未抽样子序列进行压缩,同时计算抽样子序列的伴随式。接收方利用边信息序列与未抽样子序列之间的相关性,对抽样符号进行估计,估计出的序列与原始抽样子序列的相关性得到改进。最后利用原始抽样子序列的伴随式与估计出的序列进行联合译码以重建原始抽样子序列。实验结果表明：与基于低密度奇偶校验码和算术码的DSC方案相比,该文所提方案在信源内部相关性较强时具有压缩率高、在信源间相关度不高时则有重建错误率低的特点,是一种高效、实用且易于实现的DSC方案。

     

基于原模图LDPC码的分布式联合信源信道编码

该文提出一种基于原模图低密度奇偶校验(P-LDPC)码的分布式联合信源信道编译码系统方案。该方案编码端,分布式信源发送部分信息位及校验位以同时实现压缩及纠错功能;译码端,联合迭代信源信道译码的运用进一步发掘信源的相关性以获得额外的编码增益。此外,论文研究了所提方案在译码端未知相关性系数的译码算法。仿真结果表明,所提出的基于P-LDPC码的分布式联合信源信道编译码方案在外部迭代次数不大的情况可以获得较大的性能增益,并且相关性系数在译码端已知和未知系统性能基本相当。     

采用LDPC码的分布式联合信源信道网络编码

提出了采用低密度奇偶校验码的分布式联合信源信道网络编码方案,应用于两源一中继一目的节点的无线传感器网络中.在方案中,信源节点通过传输系统信道码的校验位与部分信息位,同时实现了信源压缩与信道纠错.中继节点有效利用数据的相关性进行译码,并进行部分数据比特删余,减少因中继端网络编码引起的错误传播,仿真验证了方案的有效性.应用了不等差错保护思想,更贴近实际应用场景,利于目的节点进行更好的低误差解码.     

Distributed Source Coding in the Presence of Byzantine Sensors

The distributed source coding problem is considered when the sensors, or encoders, are under Byzantine attack; that is, an unknown group of sensors have been reprogrammed by a malicious intruder to undermine the reconstruction at the fusion center. Three different forms of the problem are considered. The first is a variable-rate setup, in which the decoder adaptively chooses the rates at which the sensors transmit. An explicit characterization of the variable-rate achievable sum rates is given for any number of sensors and any groups of traitors. The converse is proved constructively by letting the traitors simulate a fake distribution and report the generated values as the true ones. This fake distribution is chosen so that the decoder cannot determine which sensors are traitors while maximizing the required rate to decode every value. Achievability is proved using a scheme in which the decoder receives small packets of information from a sensor until its message can be decoded, before moving on to the next sensor. The sensors use randomization to choose from a set of coding functions, which makes it probabilistically impossible for the traitors to cause the decoder to make an error. Two forms of the fixed-rate problem are considered, one with deterministic coding and one with randomized coding. The achievable rate regions are given for both these problems, and it is shown that lower rates can be achieved with randomized coding.     

一种分布式信源编码中最优量化器的设计

针对传统的向量量化压缩的不足性,提高量化效果的方法主要是增加向量的维数,但同时增加了计算的复杂性.为了解决分布式编码中量化器的设计问题,在联合条件熵约束的条件下,着重从WZ量化器的最优条件分析,提出了一种Lloyd迭代算法,通过实验证明,该算法比传统的算法更可以保证量化器的局部最优性.     

On Practical Design for Joint Distributed Source and Network Coding

This paper considers the problem of communicating correlated information from multiple source nodes over a network of noiseless channels to multiple destination nodes, where each destination node wants to recover all sources. The problem involves a joint consideration of distributed compression and network information relaying. Although the optimal rate region has been theoretically characterized, it was not clear how to design practical communication schemes with low complexity. This work provides a partial solution to this problem by proposing a low-complexity scheme for the special case with two sources whose correlation is characterized by a binary symmetric channel. Our scheme is based on a careful combination of linear syndrome-based Slepian-Wolf coding and random linear mixing (network coding). It is in general suboptimal; however, its low complexity and robustness to network dynamics make it suitable for practical implementation.      

一种分簇无线传感器网络中的分布式信源编码算法

针对密集型无线传感器网络中信息存在大量冗余的问题,该文提出了一种适用于分簇无线传感网络的分布式信源编码算法。该算法以边信息作为初始参考信源,利用信源间的相关性来决定各信源的编码顺序和参考信源,然后由各信源相对于参考信源进行相关编码,接收端则根据编码顺序和参考信源进行相关译码。该文同时针对模值编码的方式,给出了一种低复杂度的译码算法。理论分析和仿真结果表明,将该算法应用于分簇路由协议中可以有效地降低节点的发送比特数,从而降低网络的能耗以延长网络寿命。     

Robust Video Transmission With Distributed Source Coded Auxiliary Channel

We propose a novel solution to the problem of robust, low-latency video transmission over lossy channels. Predictive video codecs, such as MPEG and H.26x, are very susceptible to prediction mismatch between encoder and decoder or “drift” when there are packet losses. These mismatches lead to a significant degradation in the decoded quality. To address this problem, we propose an auxiliary codec system that sends additional information alongside an MPEG or H.26x compressed video stream to correct for errors in decoded frames and mitigate drift. The proposed system is based on the principles of distributed source coding and uses the (possibly erroneous) MPEG/H.26x decoder reconstruction as side information at the auxiliary decoder. The distributed source coding framework depends upon knowing the statistical dependency (or correlation) between the source and the side information. We propose a recursive algorithm to analytically track the correlation between the original source frame and the erroneous MPEG/H.26x decoded frame. Finally, we propose a rate-distortion optimization scheme to allocate the rate used by the auxiliary encoder among the encoding blocks within a video frame. We implement the proposed system and present extensive simulation results that demonstrate significant gains in performance both visually and objectively (on the order of 2 dB in PSNR over forward error correction based solutions and 1.5 dB in PSNR over intrarefresh based solutions for typical scenarios) under tight latency constraints.      

Distributed Video Coding

Distributed coding is a new paradigm for video compression, based on Slepian and Wolf's and Wyner and Ziv's information-theoretic results from the 1970s. This paper reviews the recent development of practical distributed video coding schemes. Wyner-Ziv coding, i.e., lossy compression with receiver side information, enables low-complexity video encoding where the bulk of the computation is shifted to the decoder. Since the interframe dependence of the video sequence is exploited only at the decoder, an intraframe encoder can be combined with an interframe decoder. The rate-distortion performance is superior to conventional intraframe coding, but there is still a gap relative to conventional motion-compensated interframe coding. Wyner-Ziv coding is naturally robust against transmission errors and can be used for joint source-channel coding. A Wyner-Ziv MPEG encoder that protects the video waveform rather than the compressed bit stream achieves graceful degradation under deteriorating channel conditions without a layered signal representation.     

Distributed Arithmetic Coding

We propose a distributed binary arithmetic coder for Slepian-Wolf coding with decoder side information, along with a soft joint decoder. The proposed scheme provides several advantages over existing schemes, and its performance is equal to or better than that of an equivalent scheme based on turbo codes at short and medium block lengths.     

分布式空时编码

利用空间维度，结构简单的多节点相互协助形成的协作分集系统正成为MIMO之后又一热点。分布式空时码也在空时码的相对成熟后得到了很大发展。通过中断概率的上下界给出理论分布式空时码所达到的性能后，本文详细的阐述了最近三种分布式空时码的构造方法，达到最优的条件，运用的场合以及分集度分析。最后，本文介绍了一种简单的不采用空时编码获得满分集的方法以及它的问题。     

Hierarchical Distributed Source Coding Scheme and Optimal Transmission Scheduling for Wireless Sensor Networks

Distributed source coding (DSC) can be used to compress multiple correlated sensor measurements. These sensors send their compressed data to a central station for joint decoding. However, the issue on designing an optimal transmission scheduling scheme of DSC packets for WSNs have not been well addressed in the literature. In this work, we proposed a novel DSC coding scheme—hierarchical coding scheme, which exploits inter-node coding dependency in sensing-driven and correlated manner. In addition, the interaction between hierarchical coding topology and transmission is considered. We optimize the transmission schedule of DSC nodes to achieve better decoding quality. Our approach can be practically applied to any WSN topologies with correlated source coding nodes. Simulation shows that our work can achieve higher decoding accuracy and compression rate than previous approaches, and the decoding accuracy would not have much degradation under the error-prone wireless environment.     

Lattices for Distributed Source Coding: Jointly Gaussian Sources and Reconstruction of a Linear Function

Consider a pair of correlated Gaussian sources $(X_1,X_2)$. Two separate encoders observe the two components and communicate compressed versions of their observations to a common decoder. The decoder is interested in reconstructing a linear combination of $X_1$ and $X_2$ to within a mean-square distortion of $D$. We obtain an inner bound to the optimal rate–distortion region for this problem. A portion of this inner bound is achieved by a scheme that reconstructs the linear function directly rather than reconstructing the individual components $X_1$ and $X_2$ first. This results in a better rate region for certain parameter values. Our coding scheme relies on lattice coding techniques in contrast to more prevalent random coding arguments used to demonstrate achievable rate regions in information theory. We then consider the case of linear reconstruction of $K$ sources and provide an inner bound to the optimal rate–distortion region. Some parts of the inner bound are achieved using the following coding structure: lattice vector quantization followed by “correlated” lattice-structured binning.      

Effective Energy Adaptive and Consumption in Wireless Sensor Network Using Distributed Source Coding and Sampling Techniques

Multimedia is the process of handling multiple medium of messages over network with high rate data services in wireless cellular area networks. Communication is the process of exchanging information form one service to another. In wireless networks are significantly growth of affecting network performance and energy consumption. The major problem is end to end delay in each node and meets the quality of services. The followings are considered for implementing wireless sensor network such as reduces the network delay, propagation delay and energy consumption. The senor node can sense the encoding value and reduce the network traffic delay using mitigation method. This paper propose a unique approach to provide simple routing services with reduced traffic delay, end to end delay network performance and to achieve better performance using Distributed Source Coding and Effective Energy Consumption methods. In this paper we use optimal early detection algorithm for improving network performance and energy consumption problem. An iterative Shannon fano and Tuker method is used for finding optimal solution of each node values. Network Simulator-3 is used for simulating network environments and setup the experiments. Our proposed method shows high data rate, good performance and low energy consumptions. The results compare with existing methodologies and performance is good.

     

Source Coding for Quasiarithmetic Penalties

Whereas Huffman coding finds a prefix code minimizing mean codeword length for a given finite-item probability distribution, quasiarithmetic or quasilinear coding problems have the goal of minimizing a generalized mean of the form rho^-1(Sigma_ip_irho(l_i )), where l_i denotes the length of the ith codeword, p _i denotes the corresponding probability, and rho is a monotonically increasing cost function. Such problems, proposed by Campbell, have a number of diverse applications. Several cost functions are shown here to yield quasiarithmetic problems with simple redundancy bounds in terms of a generalized entropy. A related property, also shown here, involves the existence of optimal codes: For "well-behaved" cost functions, optimal codes always exist for (possibly infinite-alphabet) sources having finite generalized entropy. An algorithm is introduced for finding binary codes optimal for convex cost functions. This algorithm, which can be extended to other minimization utilities, can be performed using quadratic time and linear space. This reduces the computational complexity of a problem involving minimum delay in a queue, allows combinations of previously considered problems to be optimized, and greatly expands the set of problems solvable in quadratic time and linear space     

Source Coding of X-Ray Pictures

The feasibility of three specific coding schemes for compact storage or fast transmission of radiographic images is investigated. These schemes are: the synthetic high system, the block-coding system, and the run-length coding system. The last two techniques are used for encoding bit planes. The dependence of the compression ratio on image resolution and the feasibility of adaptive coding of bit planes are also examined.     

DVB中的信源压缩编码技术

本文结合ＤＶＢ实际应用，分析说明了基于ＭＰＥＧ－２的视频信源编解码器的技术特点和硬件实现的可能途径。特别对算法中几个可以改进的方面给予详细描述。