This paper presents a joint source-channel coding framework based on layered source coding and Reed-Solomon channel coding for unequal error protection. An iterative procedure is described to search for the best sourc...
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This paper presents a joint source-channel coding framework based on layered source coding and Reed-Solomon channel coding for unequal error protection. An iterative procedure is described to search for the best source coding rate and the optimal UEP of layered bitstreams. We apply our JSCC technique to transmission of JPEG-2000 coded images over binary symmetric channels. Compared to results reported in the literature, our UEP based approach gives better results while having lower complexity.
The distributed source coding problem is considered when the sensors, or encoders, are under Byzantine attack; that is, an unknown number of sensors have been reprogrammed by a malicious intruder to undermine the reco...
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ISBN:
(纸本)9781424413973;1424413974
The distributed source coding problem is considered when the sensors, or encoders, are under Byzantine attack; that is, an unknown number 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 minimum achievable sum rate is stated, given by the maximum entropy over the set of distributions indistinguishable from the true source distribution by the decoder. In addition, 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, with a larger region achievable using randomized coding, though both are suboptimal compared to variable-rate coding.
A two-terminal interactive function computation problem with alternating messages is studied within the framework of distributed block source coding theory. For any arbitrary fixed number of messages, a single-letter ...
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ISBN:
(纸本)9781424458707
A two-terminal interactive function computation problem with alternating messages is studied within the framework of distributed block source coding theory. For any arbitrary fixed number of messages, a single-letter characterization of the minimum sum-rate function was provided in previous work using traditional information-theoretic techniques. This, however, does not directly lead to a satisfactory characterization of the infinite-message limit, which is a new, unexplored dimension for asymptotic-analysis in distributed block source coding involving potentially infinitesimal-rate messages. This paper introduces a new convex-geometric approach to provide a blocklength-free single-letter characterization of the infinite-message minimum sum-rate function as a functional of the joint source pmf. This characterization is not obtained by taking a limit as the number of messages goes to infinity. Instead, it is in terms of the least element of a family of partially-ordered marginal-perturbations-concave functionals associated with the functions to be computed. For computing the Boolean AND function of two independent Bernoulli sources at one and both terminals, the respective infinite-message minimum sum-rates are characterized in closed analytic form. These sum-rates are achievable using infinitely many infinitesimal-rate messages. The convex-geometric functional viewpoint also suggests an iterative algorithm for evaluating any finite-message minimum sum-rate function.
Summary form only given. In this paper, we take a different approach from the coding community. Instead of taking the usual route of quantization plus Slepian-Wolf coding, we do not perform any Slepian-Wolf coding on ...
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ISBN:
(纸本)9781467360371
Summary form only given. In this paper, we take a different approach from the coding community. Instead of taking the usual route of quantization plus Slepian-Wolf coding, we do not perform any Slepian-Wolf coding on the transmitter side. We simply perform quantization on the sensor readings, compress the quantization indexes with conventional entropy coding, and send the compressed indexes to the receiver. On the decoder side, we simply perform entropy decoding and Gaussian process regression to reconstruct the joint source. To reduce the sum rate over all sensors, some sensors are censored and do not transmit anything to the decoder.
Summary form only given. Motivated by the correlation channel modeling problem in practical applications, such as distributed video coding, we study the binary source coding of a uniform source with side information, ...
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Summary form only given. Motivated by the correlation channel modeling problem in practical applications, such as distributed video coding, we study the binary source coding of a uniform source with side information, under asymmetric correlation channel assumptions. First, we consider the case where side information is available to both the encoder and decoder, and give an analytical formula for the rate-distortion bound. Then, we consider the side information to be available only to the decoder and present the derivation of the associated Wyner-Ziv rate-distortion bound. Most importantly, we characterize the evolution of the rate-loss suffered by Wyner-Ziv coding, for all possible binary asymmetric correlation channels.
We propose using linear mappings over finite rings as encoders in the Slepian-Wolf and the source coding for computing problems. It is known that the arithmetic of many finite rings is substantially easier to implemen...
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ISBN:
(纸本)9781479904440
We propose using linear mappings over finite rings as encoders in the Slepian-Wolf and the source coding for computing problems. It is known that the arithmetic of many finite rings is substantially easier to implement than the one of finite fields. Hence, one of the advantages of using linear mappings over rings, instead of its field counterparts, is reducing implementation complexity. More importantly, the ring version dominates the field version in terms of achieving strictly better coding rates with strictly smaller alphabet size in the source coding for computing problem [1]. This paper is dedicated to proving an achievability theorem of linear source coding over finite rings in the Slepian-Wolf problem. This result includes those given by Elias [2] and Csiszár [3] saying that linear coding over finite fields is optimal, i.e. achieves the Slepian-Wolf region. Although the optimality issue remains open, it has been verified in various scenarios including particularly many cases use non-field rings [1], [4].
An enhanced covering lemma for a Markov chain is proved in this paper, and then the distributed source coding problem of correlated general sources with one average distortion criterion under fixed-length coding is **...
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An enhanced covering lemma for a Markov chain is proved in this paper, and then the distributed source coding problem of correlated general sources with one average distortion criterion under fixed-length coding is *** on the enhanced lemma, a sufficient and necessary condition for determining the achievability of rate-distortion triples is given.
We consider the distributed source coding system of L correlated Gaussian sources Y i , i = 1,2, ⋯, L. We assume that Y L = t (Y 1 , Y 2 , ⋯, Y L ) is an observation of the remote source vector X L = t (X 1 , X 2 ...
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We consider the distributed source coding system of L correlated Gaussian sources Y i , i = 1,2, ⋯, L. We assume that Y L = t (Y 1 , Y 2 , ⋯, Y L ) is an observation of the remote source vector X L = t (X 1 , X 2 , ⋯, X L ), having the form Y L = X K + N L , where N L = t (N 1 , N 2 , ···, N L ) is a vector of L independent Gaussian random variables also independent of X L . In this system L correlated Gaussian observations are separately compressed by L encoders and sent to the information processing center. In this paper, we study the multiterminal source coding problem where the decoder wishes to reconstruct the observation Y L = X L +N L . We consider three distortion criteria based on the covariance matrix of the estimation error on Y L . For each of those three criteria we derive explicit inner and outer bounds of the rate distortion region.
An interlace coding system to avoid error propagation of source coding systems is proposed and its error performance on additive white Gaussian noise (AWGN) channel with quadrature phase shift keying (QPSK) is analyze...
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An interlace coding system to avoid error propagation of source coding systems is proposed and its error performance on additive white Gaussian noise (AWGN) channel with quadrature phase shift keying (QPSK) is analyzed. The proposed system handles data compression, data encryption and error correcting processes together, i.e. adds error correcting redundancy to the block lists of the dictionary which the compression system constructs to reduce source redundancy. The authors found that the catastrophic condition depends only on the size of the dictionary for the proposed system. Thus, by employing a large dictionary, good error performance can be obtained by the proposed system and the catastrophic condition can be avoided.< >
A description is given of studies of source coding in the specialists group on coding for visual telephony in CCITT SG XV. Using a macro block approach, the source coding algorithm will have the capability of operatin...
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A description is given of studies of source coding in the specialists group on coding for visual telephony in CCITT SG XV. Using a macro block approach, the source coding algorithm will have the capability of operating from 64 kb/s for videophone applications up to 2 Mb/s for high-quality videoconferencing applications. The authors describe the existing reference model and the evolution toward the latest reference model (RM5), which is going to be submitted for standardization. Theoretical information is provided and some examples for possible improvements are presented for the most important techniques used in the reference model, among which are quantization, variable block size, scanning classes, loop filter, entropy coding, multiple vs. single variable-length coding, and block-type discrimination.< >
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