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About 2,012 papers for “Distributed source coding”
Vikrham Gowreesunker, I. Introduction · 2008
Distributed Source Coding finds its roots in the work of Slepian-Wolf in 1973[13]. Around that time period, several other authors such as Cover, Wyner and Ziv followed up with some ground breaking extensions to other source models. After almost two decades, research in the area of Distributed Source Coding was reborn because of the growing
Cited by 0
Gerhard Maierbacher, João Barros · Globecom · 2006
Motivated by the design of low-complexity distributed quantizers and iterative decoding algorithms that leverage the correlation in the data picked up by a large-scale sensor network, we address the problem of finding correlation preserving clusters. To construct a factor graph describing the statistical dependencies between sensor measurements, we develop a hierarchical clustering algorithm that minimizes the Kullback Leibler distance between known and approximated source statistics. Finally, we show how the clustering result can be exploited in the design of index assignments for distributed quantization and source-channel decoders of manageable complexity.
Cited by 6
David Varodayan, Yao-Chung Lin, Bernd Girod · Proceedings of the ... IEEE International Conference on Acoustics, Speech, and Signal Processing · 2008
Audio authentication is important in content delivery via untrusted intermediaries, for example peer-to-peer (P2P) file sharing. Many differently encoded versions of the original audio might exist. Distinguishing the legitimate diversity of encodings from malicious tampering is the challenge addressed in this paper. We develop an approach based on distributed source coding for the problem of backward-compatible audio authentication. The key idea is to provide a Slepian-Wolf encoded quantized perceptually significant audio projection as authentication data. This version can be correctly decoded only with the help of authentic audio as side information. Distributed source coding provides the desired robustness against legitimate encoding variations, while detecting illegitimate modification. We demonstrate reliable authentication at a Slepian-Wolf bitrate of less than 100 bit/s.
Cited by 10
Mahesh Mahadevan · Figshare · 2022
In their 1973 paper Slepian and Wolf described the achievable rate region for two correlated sources transmitting to a common destination over noiseless channels. The important case of distributed source coding, i.e where the encoding is done separately and the decoding is done jointly, is considered. In this thesis, we extend this scenario to the case where the channels are noisy. Distributed coding schemes are proposed for the transmission of both discrete valued and continuous valued sources over noisy channels. The schemes rely on iterative decoding at the receiver. First the case of two correlated continuous valued sources transmitting to a common destination is discussed. The encoding scheme consists of a variable length encoder at one source and a convolutional encoder at the other source. An iterative decoder is derived for this encoding scheme which is similar to the decoder of a parallel concatenated code. Two different correlation models are considered: a binary symmetric channel correlation model and a Gaussian correlation model. The proposed scheme is compared to an alternate scheme employing convolutional codes at each source in terms of symbol error rate and mean square error. In both cases, the proposed scheme is seen to give better performance for sources exhibiting low correlation. Next, the transmission of a binary source over a noisy channel when a correlated source is available at the receiver as side information is considered. A coding scheme which is a concatenation of an outer irregular repeat code with an inner convolutional code is proposed. A novel EXIT chart based optimization criterion is proposed to design the code parameters. The performance of codes designed using the proposed approach is seen to be close to theoretical bounds.
Cited by 0Open access
Guogang Hua, Chang Wen Chen · 2005
This paper offers a practical distributed data compression in wireless sensor networks based on convolutional code and turbo code. An improved Viterbi algorithm for distributed source coding (VA-DSC) is proposed to take the advantage of the known parity bits at the decoder. When the algorithm is applied to recursive systematic convolutional (RSC) and turbo codes, it can decrease both the decoding error probability and the computation complexity. Also a scheme of applying distributed source coding to wireless sensor networks is proposed to ensure receiving the data correctly as well as reducing the energy consumption in the networks.
Cited by 21
Hui Chen, Lizhen Wang · 2024
Considering the shortcomings of distributed source coding (DSC) in quantum communication, such as the high bit error rate and low compression ratio, an improved distributed source coding is proposed in this paper. In the design of the source encoder, redundancy technology is used to provide error protection, and then the joint design of Low-Density Parity Check code (LDPC) with redundancy is adopted to conduct distributed source coding. Experiment results show that the proposed method can be kept the compression ratio well and be easily implemented when a strong internal correlation of the quantum communication areas. The the reconstructed sequence can reach low bit error rate when the correlation between sources are weak. It is a practical, efficient DSC scheme.
Cited by 0
Virendra K. Varshneya, Vinod Sharma · 2008
In a typical sensor network scenario a goal is to monitor a spatio-temporal process through a number of inexpensive sensing nodes, the key parameter being the fidelity at which the process has to be estimated at distant locations. We study such a scenario in which multiple encoders transmit their correlated data at finite rates to a distant and common decoder. In particular, we derive inner and outer bounds on the rate region for the random field to be estimated with a given mean distortion.
Cited by 0
Maddah-Ali, Mohammad Ali, Author, Tse, David, Author · UC Berkeley
We consider a problem of distributed lossy source coding with three jointly Gaussian sources (y1,y2,y3), where y1 and y2 are positively correlated, y3=y1-cy2, c >=0, and the decoder requires reconstructing y3 with a target distortion. Inspired by results from the binary expansion model, the rate-distortion region of this problem is characterized within a bounded gap. Treating each source as a multi-layer input, it is shown that the layers required by the decoder are combined with some unneeded information, referred as interference. Therefore, the responsibility of a source coding algorithm is not only to eliminate the redundancy among the inputs, but also to manage the interference. It is shown that the interference can be effectively managed through some linear operations among the input layers. Binary expansion model demonstrates that some middle layers of y1 and y2 are not needed at the decoder, while some upper and lower layers are required. Structured (Lattice) quantizers enable the encoders to pre-eliminate unnecessary layers. While in the lossless distributed source coding cut-set outer bound is tight, it is shown that in the lossy ones, even for binary expansion models, this outer-bound has an unbounded gap with the rate distortion region. To prove the bounded-gap result, a new outer-bound is established.
Cited by 0
Vladimir Stanković, Yang Yang, Zixiang Xiong · 2007
We propose a system for real-time multimedia multicast over heterogeneous wireless-wireline networks. The encoded source is transmitted from the base station over the wireless radio link to numerous Internet servers. Each server performs distributed source coding (as quantization followed by Slepian-Wolf coding) by exploiting mutual correlation among packets received at different servers. The resulting packets are forwarded to the clients for joint decoding. We provide an algorithm for optimal nonuniform scalar quantizers design at the server side that minimizes the required rate under the decoder bit error rate constraint. For scalable multimedia codes, we develop joint source-channel coding scheme which combines error-protection at the base station and distributed source coding at the servers. Our experimental results show significant performance improvements over conventional solutions due to spatial diversity and distributed source coding gains.
Cited by 1
Akshay Kashyap, L. A. Lastras-Montaño, Cathy H. Xia et al. · ArXiv.org · 2007
We study the problem of the reconstruction of a Gaussian field defined in [0,1] using N sensors deployed at regular intervals. The goal is to quantify the total data rate required for the reconstruction of the field with a given mean square distortion. We consider a class of two-stage mechanisms which a) send information to allow the reconstruction of the sensor's samples within sufficient accuracy, and then b) use these reconstructions to estimate the entire field. To implement the first stage, the heavy correlation between the sensor samples suggests the use of distributed coding schemes to reduce the total rate. We demonstrate the existence of a distributed block coding scheme that achieves, for a given fidelity criterion for the reconstruction of the field, a total information rate that is bounded by a constant, independent of the number $N$ of sensors. The constant in general depends on the autocorrelation function of the field and the desired distortion criterion for the sensor samples. We then describe a scheme which can be implemented using only scalar quantizers at the sensors, without any use of distributed source coding, and which also achieves a total information rate that is a constant, independent of the number of sensors. While this scheme operates at a rate that is greater than the rate achievable through distributed coding and entails greater delay in reconstruction, its simplicity makes it attractive for implementation in sensor networks.
Cited by 0Open access
R. S. Raja Durai · 2006
Distributed source coding is a general framework that applies to sensor networks. Recently, considerable research on the distributed source coding of correlated sources have rekindled research scientists and engineers because of its possible application to video compression. In the sequel, distributed source coding methods like DISCUS (distributed source coding using syndromes), PRISM (power efficient, robust, high compression, syndrome-based multimedia coding) are developed which aim at compression of sequence of images. This paper gives a construction to a class of T-direct codes with constituent codes are derived from the class of rank distance codes and presents yet another approach to distributed source coding of two correlated sources X, Y isin F <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">n</sup> using a class of multi-user codes, namely T-direct codes, where T les n and F being an arbitrary field
Cited by 1
Mohammad Ali Maddah-Ali, David Tse · 2010
We consider a problem of distributed lossy Gaussian source coding with inputs (y <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> , y <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> , y <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sub> ), where y <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> and y <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> are positively correlated, y <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sub> = y <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> - cy <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> , c ≥ 0, and the decoder requires y <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sub> with a target distortion. For this problem, known achievable schemes are unboundedly loose. Inspired by results of binary expansion models, we characterize the rate-distortion region within a bounded gap. Treating each source as a multilayer input, an achievable scheme is developed based on the following observations: (i) some middle layers of y <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> and y <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> are not needed at the decoder, (ii) the required layers are combined with some unneeded interference information, (iii) linear operations among input layers can unboundedly reduce the load of reporting interference. Showing that the cut-set outer-bound has an unbounded gap, we also establish a new outer-bound to prove the bounded-gap result.
Cited by 22
Yao-Chung Lin, David Varodayan, Bernd Girod · 2007
Image authentication is important in content delivery via untrusted intermediaries, such as peer-to-peer (P2P) file sharing. Many differently encoded versions of the original image might exist. On the other hand, intermediaries might tamper with the contents. Distinguishing the legitimate diversity of encodings from malicious manipulation is the challenge addressed in this paper. We develop a novel approach based on distributed source coding for the problem of backward-compatible image authentication. The key idea is to provide a Slepian-Wolf encoded quantized image projection as authentication data. This version can be correctly decoded only with the help of an authentic image as side information. Distributed source coding provides the desired robustness against legitimate encoding variations, while detecting illegitimate modification. We demonstrate false acceptance rates close to zero for authentication data sizes that are only a few percent of the compressed image size.
Cited by 56
David Varodayan, Anne Aaron, Bernd Girod · Signal Processing · 2006
Cited by 322
Min Ye, Alexander Barg · Advances in Mathematics of Communications · 2015
We show that polar codes can be used to achieve the rate-distortion functions in the problemof hierarchical source coding also known as the successive refinement problem. We also analyze the distributedversion of this problem, constructing a polar coding scheme that achieves the rate distortion functionsfor successive refinement with side information.
Cited by 7Open access
John Z. Sun, Vivek K Goyal · 2013
For point-to-point and distributed communication of continuous sources, high-resolution quantization theory provides an achievable rate-distortion trade-off that is simple to compute and motivates practical compression architectures. Moreover, high-resolution analysis gives good inner bounds for the Shannon rate-distortion region when a more general characterization is difficult. In this paper, we analyze the sum-rate gap between coded nonuniform scalar quantization and the Shannon rate- distortion region for a system that requires fidelity in a computation applied to the source variables. We find that the loss can be as low as 0.255 bits/sample, which has previously been observed in the point-to-point setting, and it is achieved using a simple architecture of nonuniform quantization followed by Slepian-Wolf coding.
Cited by 0
Mehrdad Teratani, Toshiaki Fujii, Masayuki Tanimoto · Dépôt institutionnel de l'Université libre de Bruxelles (Université Libre de Bruxelles) · 2003
info:eu-repo/semantics/published
Cited by 0
Mina Sartipi, Faramarz Fekri · IEEE Communications Letters · 2009
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.
Cited by 2
L. Di Paolo, C. Fischione, F. Graziosi et al. · 2006
Abstract — In this paper, we propose a theoretical setup for evaluation of energy efficiency of wireless sensor networks (WSNs) with distributed source coding (DSC) algorithms and packet aggregation (PA). We consider four topologies for DSC and three alternatives for PA, and the system model includes a realistic network architecture with multi-hop communication, automatic repeat request protocol (ARQ), and packet losses. The analysis is carried out in two steps. Firstly we derive the packet loss probability, and then evaluate the average number of packets transmitted throughout the network. This second performance index can then be mapped onto an energy efficiency indicator. The proposed model is specifically adopted for performance comparison of the different coding strategies and aggregation schemes in terms of energy efficiency. Numerical results show that packet overheads have a relevant influence on performance, while the ARQ protocol introduces negligible effects on the energy consumption. Furthermore, DSC topologies with masterslave approach and fragmentation of packets exhibit better performance.
Cited by 0
Grégory Huchet, Jean‐Yves Chouinard, Demin Wang et al. · 2009
In the last few years distributed video coding (DVC) has become a new paradigm for video compression where the encoding process needs to be simple. DVC allows for the development of new applications where the computational complexity and the amount of memory inside the video encoder are limited. In this paper, we introduce a new data representation and coding method for DVC systems. The proposed method consists of an adaptive binary representation based on the maximum difference between the source picture and the side information. This adaptive representation provides a reduction of bitrate without any loss of information, while maintaining the low complexity of the encoder. Experimental results show a significant increase in performance over conventional DVC methods.
Cited by 11