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Jun Chen - One of the best experts on this subject based on the ideXlab platform.

  • Index Mapping for Bit-Error Resilient Multiple Description Lattice Vector Quantizer
    IEEE Transactions on Communications, 2018
    Co-Authors: Yifang Chen, Jun Chen
    Abstract:

    In conventional multiple description coding (MDC), two descriptions of a source are generated and sent over ON/OFF Channels. In this paper, we are interested in exploiting the redundancy built in MDC to additionally confer robustness against other Channel errors. In particular, we consider a multiple description lattice vector quantizer (MDLVQ) whose output (a pair of side lattice points) is mapped to a pair of binary indexes and each index is sent over a binary Channel. One Channel is noiseless, while the other is noisy. Thus, at the deCoder, one description is received error-free, while the other may carry bit errors. Then the deCoder uses the error-free description as side information to improve the reconstruction. The effectiveness of the deCoder in alleviating the impact of bit errors depends on the mapping $\gamma $ of side lattice points to binary indexes. We propose the design of a structured bit-error resilient mapping $\gamma $ . For this, the set of side lattice points is first partitioned using Voronoi regions of an appropriate coarse lattice. Next a good linear Channel Code is selected, each Voronoi region is assigned a coset of this Channel Code, and the side lattice points within each Voronoi region are mapped to binary sequences in the corresponding coset. In addition, we argue that the performance of $\gamma $ is improved by assigning cosets close in Hamming distance to neighboring Voronoi regions, and propose a technique to achieve this goal. We derive a lower bound on the error correction performance of the proposed mapping $\gamma $ in terms of the performance of the Channel Code $C$ used in its construction. Interestingly, we prove that, as the rate of the MDLVQ grows to infinity, the mapping $\gamma $ becomes as good as the Code $C$ in correcting bit errors. Simulation results show the significant superiority of the proposed index mapping versus random mappings.

  • index mapping for bit error resilient multiple description lattice vector quantizer
    International Symposium on Information Theory, 2017
    Co-Authors: Sorina Dumitrescu, Yifang Chen, Jun Chen
    Abstract:

    This work addresses the construction of bit-error resilient multiple description lattice vector quantizers (MDLVQ) by proposing the design of a structured mapping γ of side lattice points to binary indexes. We assume that the first description is correct while the second description may carry bit errors. To design the mapping γ the set of side lattice points is first partitioned into Voronoi regions of an appropriate coarse lattice. Next a good Channel Code C is selected, each Voronoi region is assigned a coset of this Channel Code and the side lattice points within each Voronoi region are mapped to binary sequences in the corresponding coset. We derive a lower bound on the error correction performance of the mapping γ in terms of the performance of the Code C and we show that, as the rate of the MDLVQ grows to i, the mapping γ becomes as good as the Code C. Simulation results show the significant superiority of the proposed mapping versus random mappings.

Yifang Chen - One of the best experts on this subject based on the ideXlab platform.

  • Index Mapping for Bit-Error Resilient Multiple Description Lattice Vector Quantizer
    IEEE Transactions on Communications, 2018
    Co-Authors: Yifang Chen, Jun Chen
    Abstract:

    In conventional multiple description coding (MDC), two descriptions of a source are generated and sent over ON/OFF Channels. In this paper, we are interested in exploiting the redundancy built in MDC to additionally confer robustness against other Channel errors. In particular, we consider a multiple description lattice vector quantizer (MDLVQ) whose output (a pair of side lattice points) is mapped to a pair of binary indexes and each index is sent over a binary Channel. One Channel is noiseless, while the other is noisy. Thus, at the deCoder, one description is received error-free, while the other may carry bit errors. Then the deCoder uses the error-free description as side information to improve the reconstruction. The effectiveness of the deCoder in alleviating the impact of bit errors depends on the mapping $\gamma $ of side lattice points to binary indexes. We propose the design of a structured bit-error resilient mapping $\gamma $ . For this, the set of side lattice points is first partitioned using Voronoi regions of an appropriate coarse lattice. Next a good linear Channel Code is selected, each Voronoi region is assigned a coset of this Channel Code, and the side lattice points within each Voronoi region are mapped to binary sequences in the corresponding coset. In addition, we argue that the performance of $\gamma $ is improved by assigning cosets close in Hamming distance to neighboring Voronoi regions, and propose a technique to achieve this goal. We derive a lower bound on the error correction performance of the proposed mapping $\gamma $ in terms of the performance of the Channel Code $C$ used in its construction. Interestingly, we prove that, as the rate of the MDLVQ grows to infinity, the mapping $\gamma $ becomes as good as the Code $C$ in correcting bit errors. Simulation results show the significant superiority of the proposed index mapping versus random mappings.

  • index mapping for bit error resilient multiple description lattice vector quantizer
    International Symposium on Information Theory, 2017
    Co-Authors: Sorina Dumitrescu, Yifang Chen, Jun Chen
    Abstract:

    This work addresses the construction of bit-error resilient multiple description lattice vector quantizers (MDLVQ) by proposing the design of a structured mapping γ of side lattice points to binary indexes. We assume that the first description is correct while the second description may carry bit errors. To design the mapping γ the set of side lattice points is first partitioned into Voronoi regions of an appropriate coarse lattice. Next a good Channel Code C is selected, each Voronoi region is assigned a coset of this Channel Code and the side lattice points within each Voronoi region are mapped to binary sequences in the corresponding coset. We derive a lower bound on the error correction performance of the mapping γ in terms of the performance of the Code C and we show that, as the rate of the MDLVQ grows to i, the mapping γ becomes as good as the Code C. Simulation results show the significant superiority of the proposed mapping versus random mappings.

Jun Muramatsu - One of the best experts on this subject based on the ideXlab platform.

  • construction of a Channel Code from an arbitrary source Code with deCoder side information
    International Symposium on Information Theory and its Applications, 2016
    Co-Authors: Jun Muramatsu, Shigeki Miyake
    Abstract:

    The construction of a Channel Code by using a source Code with deCoder side information is introduced. For the construction, any pair of enCoder and deCoder is available for a source Code with deCoder side information. A constrained-random-number generator, which generates random numbers satisfying a condition specified by a function and its value, is used to construct a stochastic Channel enCoder. The result suggests that we can divide the Channel coding problem into the problems of Channel encoding and source decoding with side information.

  • construction of strongly secure wiretap Channel Code based on hash property
    International Symposium on Information Theory, 2011
    Co-Authors: Jun Muramatsu, Shigeki Miyake
    Abstract:

    A strongly secure wiretap Channel Code is proposed. The construction is based on the strong hash property introduced in Proc. ISIT2010, pp. 575–579. Since an ensemble of sparse matrices satisfies the conditions for the strong hash property, the rate of the proposed Code using sparse matrices can achieve the secrecy capacity.

  • construction of slepian wolf source Code and broadcast Channel Code based on hash property
    arXiv: Information Theory, 2010
    Co-Authors: Jun Muramatsu, Shigeki Miyake
    Abstract:

    The aim of this paper is to prove theorems for the Slepian-Wolf source coding and the broadcast Channel coding (independent messages and no common message) based on the the notion of a stronger version of the hash property for an ensemble of functions. Since an ensemble of sparse matrices has a strong hash property, Codes using sparse matrices can realize the achievable rate region. Furthermore, extensions to the multiple source coding and multiple output broadcast Channel coding are introduced.

  • Construction of broadcast Channel Code based on hash property
    2010 IEEE International Symposium on Information Theory, 2010
    Co-Authors: Jun Muramatsu, Shigeki Miyake
    Abstract:

    The aim of this paper is to construct a Code for broadcast Channel (independent messages and no common message) based on the the notion of a stronger version of the hash property for an ensemble of functions. Since an ensemble of sparse matrices has a strong hash property, Codes using sparse matrices can achieve an inner bound of capacity region.

  • A Construction of Channel Code, Joint Source-Channel Code, and Universal Code for Arbitrary Stationary Memoryless Channels Using Sparse Matrices
    IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences, 2009
    Co-Authors: Shigeki Miyake, Jun Muramatsu
    Abstract:

    A Channel Code is constructed using sparse matrices for stationary memoryless Channels that do not necessarily have a symmetric property like a binary symmetric Channel. It is also shown that the constructed Code has the following remarkable properties. 1. Joint source-Channel coding: Combining Channel Code with lossy source Code, which is also constructed by sparse matrices, a simpler joint source-Channel Code can be constructed than that constructed by the ordinary block Code. 2. Universal coding: The constructed Channel Code has a universal property under a specified condition.

Shigeki Miyake - One of the best experts on this subject based on the ideXlab platform.

  • construction of a Channel Code from an arbitrary source Code with deCoder side information
    International Symposium on Information Theory and its Applications, 2016
    Co-Authors: Jun Muramatsu, Shigeki Miyake
    Abstract:

    The construction of a Channel Code by using a source Code with deCoder side information is introduced. For the construction, any pair of enCoder and deCoder is available for a source Code with deCoder side information. A constrained-random-number generator, which generates random numbers satisfying a condition specified by a function and its value, is used to construct a stochastic Channel enCoder. The result suggests that we can divide the Channel coding problem into the problems of Channel encoding and source decoding with side information.

  • construction of strongly secure wiretap Channel Code based on hash property
    International Symposium on Information Theory, 2011
    Co-Authors: Jun Muramatsu, Shigeki Miyake
    Abstract:

    A strongly secure wiretap Channel Code is proposed. The construction is based on the strong hash property introduced in Proc. ISIT2010, pp. 575–579. Since an ensemble of sparse matrices satisfies the conditions for the strong hash property, the rate of the proposed Code using sparse matrices can achieve the secrecy capacity.

  • construction of slepian wolf source Code and broadcast Channel Code based on hash property
    arXiv: Information Theory, 2010
    Co-Authors: Jun Muramatsu, Shigeki Miyake
    Abstract:

    The aim of this paper is to prove theorems for the Slepian-Wolf source coding and the broadcast Channel coding (independent messages and no common message) based on the the notion of a stronger version of the hash property for an ensemble of functions. Since an ensemble of sparse matrices has a strong hash property, Codes using sparse matrices can realize the achievable rate region. Furthermore, extensions to the multiple source coding and multiple output broadcast Channel coding are introduced.

  • Construction of broadcast Channel Code based on hash property
    2010 IEEE International Symposium on Information Theory, 2010
    Co-Authors: Jun Muramatsu, Shigeki Miyake
    Abstract:

    The aim of this paper is to construct a Code for broadcast Channel (independent messages and no common message) based on the the notion of a stronger version of the hash property for an ensemble of functions. Since an ensemble of sparse matrices has a strong hash property, Codes using sparse matrices can achieve an inner bound of capacity region.

  • A Construction of Channel Code, Joint Source-Channel Code, and Universal Code for Arbitrary Stationary Memoryless Channels Using Sparse Matrices
    IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences, 2009
    Co-Authors: Shigeki Miyake, Jun Muramatsu
    Abstract:

    A Channel Code is constructed using sparse matrices for stationary memoryless Channels that do not necessarily have a symmetric property like a binary symmetric Channel. It is also shown that the constructed Code has the following remarkable properties. 1. Joint source-Channel coding: Combining Channel Code with lossy source Code, which is also constructed by sparse matrices, a simpler joint source-Channel Code can be constructed than that constructed by the ordinary block Code. 2. Universal coding: The constructed Channel Code has a universal property under a specified condition.

Victoria Kostina - One of the best experts on this subject based on the ideXlab platform.

  • lossy joint source Channel coding in the finite blocklength regime
    IEEE Transactions on Information Theory, 2013
    Co-Authors: Victoria Kostina
    Abstract:

    This paper finds new tight finite-blocklength bounds for the best achievable lossy joint source-Channel Code rate, and demonstrates that joint source-Channel Code design brings considerable performance advantage over a separate one in the nonasymptotic regime. A joint source-Channel Code maps a block of k source symbols onto a length-n Channel Codeword, and the fidelity of reproduction at the receiver end is measured by the probability e that the distortion exceeds a given threshold d. For memoryless sources and Channels, it is demonstrated that the parameters of the best joint source-Channel Code must satisfy nC - kR(d) ≈ √(nV + k V(d)) Q-1(e), where C and V are the Channel capacity and Channel dispersion, respectively; R(d) and V(d) are the source rate-distortion and rate-dispersion functions; and Q is the standard Gaussian complementary cumulative distribution function. Symbol-by-symbol (unCoded) transmission is known to achieve the Shannon limit when the source and Channel satisfy a certain probabilistic matching condition. In this paper, we show that even when this condition is not satisfied, symbol-by-symbol transmission is, in some cases, the best known strategy in the nonasymptotic regime.

  • lossy joint source Channel coding in the finite blocklength regime
    arXiv: Information Theory, 2012
    Co-Authors: Victoria Kostina
    Abstract:

    This paper finds new tight finite-blocklength bounds for the best achievable lossy joint source-Channel Code rate, and demonstrates that joint source-Channel Code design brings considerable performance advantage over a separate one in the non-asymptotic regime. A joint source-Channel Code maps a block of $k$ source symbols onto a length$-n$ Channel Codeword, and the fidelity of reproduction at the receiver end is measured by the probability $\epsilon$ that the distortion exceeds a given threshold $d$. For memoryless sources and Channels, it is demonstrated that the parameters of the best joint source-Channel Code must satisfy $nC - kR(d) \approx \sqrt{nV + k \mathcal V(d)} Q(\epsilon)$, where $C$ and $V$ are the Channel capacity and Channel dispersion, respectively; $R(d)$ and $\mathcal V(d)$ are the source rate-distortion and rate-dispersion functions; and $Q$ is the standard Gaussian complementary cdf. Symbol-by-symbol (unCoded) transmission is known to achieve the Shannon limit when the source and Channel satisfy a certain probabilistic matching condition. In this paper we show that even when this condition is not satisfied, symbol-by-symbol transmission is, in some cases, the best known strategy in the non-asymptotic regime.

  • lossy joint source Channel coding in the finite blocklength regime
    International Symposium on Information Theory, 2012
    Co-Authors: Victoria Kostina
    Abstract:

    This paper shows new tight finite-blocklength bounds for the best achievable lossy joint sour ce-Channel Code rate, and demonstrates that joint sour ce-Channel Code design brings considerable performance advantage over a separate one in the non-asymptotic regime. A joint source-Channel Code maps a block of k source symbols onto a length — n Channel Codeword, and the fidelity of reproduction at the receiver end is measured by the probability ∊ that the distortion exceeds a given threshold d. For memoryless sources and Channels, it is demonstrated that the parameters of the best joint source-Channel Code must satisfy nC − kR(d) ≈ √nV + kV(d) Q−1 (∊), where C and V are the Channel capacity and dispersion, respectively; R(d) and V(d) are the source rate-distortion and rate-dispersion functions; and Q is the standard Gaussian complementary cdf.

  • Lossy joint source-Channel coding in the finite blocklength regime,” arXiv preprint cs/1209.1317v1
    2012
    Co-Authors: Victoria Kostina, Sergio Verdú
    Abstract:

    Abstract—This paper shows new tight finite-blocklength bounds for the best achievable lossy joint source-Channel Code rate, and demonstrates that joint source-Channel Code design brings considerable performance advantage over a separate one in the non-asymptotic regime. A joint source-Channel Code maps ablockofk source symbols onto a length−n Channel Codeword, and the fidelity of reproduction at the receiver end is measured by the probability ɛ that the distortion exceeds a given threshold d. FormemorylesssourcesandChannels,itisdemonstratedthat the parameters of the best joint source-Channel Code must satisfy nC − kR(d) ≈ p nV + kV(d)Q −1 (ɛ), whereC and V are the Channel capacity and dispersion, respectively; R(d) and V(d) are the source rate-distortion and rate-dispersion functions; andQ is the standard Gaussian complementary cdf. Index Terms—Achievability, converse, finite blocklength regime, joint source-Channel coding, lossy source coding, memoryless sources, rate-distortion theory, Shannon theory. I