Density Evolution for the Design of Non-Binary Low Density Parity Check Codes for Slepian-Wolf Coding

International audienceIn this paper, we investigate the problem of designing good non-binary LDPC codes for Slepian-Wolf coding. The design method is based on Density Evolution which gives the asymptotic error probability of the decoder for given code degree distributions. Density Evolution was originally introduced for channel coding under the assumption that the channel is symmetric. In Slepian-Wolf coding, the correlation channel is not necessarily symmetric and the source distribution has to be taken into account. In this paper, we express the non-binary Density Evolution recursion for Slepian-Wolf coding. From Density Evolution, we then perform code degree distribution optimization using an optimization algorithm called differential evolution. Both asymptotic performance evaluation and finite-length simulations show the gain at considering optimized degree distributions for SW coding

Lossless Source Coding in the Point-to-Point, Multiple Access, and Random Access Scenarios

This paper treats point-to-point, multiple access and random access lossless source coding in the finite-blocklength regime. A random coding technique is developed, and its power in analyzing the third-order coding performance is demonstrated in all three scenarios. Via a connection to composite hypothesis testing, a new converse that tightens previously known converses for Slepian-Wolf source coding is established. Asymptotic results include a third-order characterization of the Slepian-Wolf rate region and a proof showing that for dependent sources, the independent encoders used by Slepian-Wolf codes can achieve the same third-order-optimal performance as a single joint encoder. The concept of random access source coding, which generalizes the multiple access scenario to allow for a subset of participating encoders that is unknown a priori to both the encoders and the decoder, is introduced. Contributions include a new definition of the probabilistic model for a random access source, a general random access source coding scheme that employs a rateless code with sporadic feedback, and an analysis demonstrating via a random coding argument that there exists a deterministic code of the proposed structure that simultaneously achieves the third-order-optimal performance of Slepian-Wolf codes for all possible subsets of encoders.Comment: 42 pages, 10 figures. Part of this work was presented at ISIT'1

Source Polarization

The notion of source polarization is introduced and investigated. This complements the earlier work on channel polarization. An application to Slepian-Wolf coding is also considered. The paper is restricted to the case of binary alphabets. Extension of results to non-binary alphabets is discussed briefly.Comment: To be presented at the IEEE 2010 International Symposium on Information Theory

Networked Slepian-Wolf: theory, algorithms, and scaling laws

Consider a set of correlated sources located at the nodes of a network, and a set of sinks that are the destinations for some of the sources. The minimization of cost functions which are the product of a function of the rate and a function of the path weight is considered, for both the data-gathering scenario, which is relevant in sensor networks, and general traffic matrices, relevant for general networks. The minimization is achieved by jointly optimizing a) the transmission structure, which is shown to consist in general of a superposition of trees, and b) the rate allocation across the source nodes, which is done by Slepian-Wolf coding. The overall minimization can be achieved in two concatenated steps. First, the optimal transmission structure is found, which in general amounts to finding a Steiner tree, and second, the optimal rate allocation is obtained by solving an optimization problem with cost weights determined by the given optimal transmission structure, and with linear constraints given by the Slepian-Wolf rate region. For the case of data gathering, the optimal transmission structure is fully characterized and a closed-form solution for the optimal rate allocation is provided. For the general case of an arbitrary traffic matrix, the problem of finding the optimal transmission structure is NP-complete. For large networks, in some simplified scenarios, the total costs associated with Slepian-Wolf coding and explicit communication (conditional encoding based on explicitly communicated side information) are compared. Finally, the design of decentralized algorithms for the optimal rate allocation is analyzed

Studying error resilience performance for a feedback channel based transform domain Wyner-Ziv video codec

Wyner-Ziv (WZ) video coding is an emerging video coding paradigm based on two major Information Theory results: the Slepian-Wolf and Wyner-Ziv theorems. One of the most interesting and used WZ video i coding architectures makes use of a feedback channel (FC) to perform c rate control at the decoder; in this context, the Slepian-Wolf coding t module is typically based on turbo coding with puncturing. Because WZ coding is not based on the prediction loop used in conventional video coding but rather on a statistical approach where a decoder estimation of the frame to be coded is 'corrected' by the encoder, it provides intrinsic error resilience capabilities. This paper intends to study the error resilience performance of a feedback channel based transform domain WZ codec using appropriate scenarios and conditions, notably in comparison with the best performing H. 264/AVC standard.info:eu-repo/semantics/acceptedVersio