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nchannel symmetric multipledescription lattice vector quantization
 in Proc. Data Compression Conf
, 2005
"... We derive analytical expressions for the central and side quantizers in an nchannel symmetric multipledescription lattice vector quantizer which, under highresolution assumptions, minimize the expected distortion subject to entropy constraints on the side descriptions for given packetloss probab ..."
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Cited by 6 (3 self)
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We derive analytical expressions for the central and side quantizers in an nchannel symmetric multipledescription lattice vector quantizer which, under highresolution assumptions, minimize the expected distortion subject to entropy constraints on the side descriptions for given packetloss probabilities. The performance of the central quantizer is lattice dependent whereas the performance of the side quantizers is lattice independent. In fact the normalized second moments of the side quantizers are given by that of an Ldimensional sphere. Furthermore, our analytical results reveal a simple way to determine the optimum number of descriptions. We verify theoretical results with numerical experiments and show that with a packetloss probability of 5%, a gain of 9.1 dB in MSE over stateoftheart twodescription systems can be achieved when quantizing a twodimensional unitvariance Gaussian source using a total bit budget of 15 bits/dimension and using three descriptions. With 20 % packet loss, a similar experiment reveals an MSE reduction of 10.6 dB when using four descriptions. 1
Multipledescription coding by dithered deltasigma quantization
 in Data Compression Conference, 2007. DCC ’07, (Snowbird, UT
, 2007
"... We address the connection between the multipledescription (MD) problem and DeltaSigma quantization. The inherent redundancy due to oversampling in DeltaSigma quantization, and the simple linearadditive noise model resulting from dithered lattice quantization, allow us to construct a symmetric and ..."
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Cited by 4 (1 self)
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We address the connection between the multipledescription (MD) problem and DeltaSigma quantization. The inherent redundancy due to oversampling in DeltaSigma quantization, and the simple linearadditive noise model resulting from dithered lattice quantization, allow us to construct a symmetric and timeinvariant MD coding scheme. We show that the use of a noise shaping filter makes it possible to trade off central distortion for side distortion. Asymptotically as the dimension of the lattice vector quantizer and order of the noise shaping filter approach infinity, the entropy rate of the dithered DeltaSigma quantization scheme approaches the symmetric twochannel MD ratedistortion function for a memoryless Gaussian source and MSE fidelity criterion, at any sidetocentral distortion ratio and any resolution. In the optimal scheme, the infiniteorder noise shaping filter must be minimum phase and have a piecewise flat power spectrum with a single jump discontinuity. An important advantage of the proposed design is that it is symmetric in rate and distortion by construction, so the coding rates of the descriptions are identical and there is therefore no need for source splitting. Index Terms deltasigma modulation, dithered lattice quantization, entropy coding, joint sourcechannel coding, multipledescription coding, vector quantization. I.
RATE DISTRIBUTION BETWEEN MODEL AND SIGNAL FOR MULTIPLE DESCRIPTIONS
"... We consider the rate allocation problem for multipledescription quantization of the signal described by an adaptive model with a fixed structure. The source modeling in coding generally results in a twostage description of the data, where one of the stages describes the model parameters, and the o ..."
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We consider the rate allocation problem for multipledescription quantization of the signal described by an adaptive model with a fixed structure. The source modeling in coding generally results in a twostage description of the data, where one of the stages describes the model parameters, and the other describes the signal. Such a setup implies the existence of a tradeoff between the rate spent on the parameters and the rate spent on the signal. We optimize this tradeoff analytically for the multipledescription case using a method inspired by Minimum Description Length principle. We also provide an algorithm for optimizing the rate allocation between the components of the modelbased multiple description coder. Finally we experimentally confirm our results. Our method facilitates the rateadaptive multipledescription coding. Index Terms — source modeling, multiple description coding (MDC), audio coding. 1.
ASYMPTOTIC ANALYSIS OF MULTIPLE DESCRIPTION LATTICE VECTOR QUANTIZATION
"... Recent results have shown that general Kchannel multipledescriptioncoding (MDC) approaches often have significant advantages over conventional twochannel MDC methods. We provide new asymptotic results to describe the performance of a general Kchannel symmetric MDC lattice vector quantizer (MDLVQ ..."
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Recent results have shown that general Kchannel multipledescriptioncoding (MDC) approaches often have significant advantages over conventional twochannel MDC methods. We provide new asymptotic results to describe the performance of a general Kchannel symmetric MDC lattice vector quantizer (MDLVQ). We consider a memoryless Ldimensional source with probability density function f and differential entropy h(f) <∞. We control the redundancy with a parameter a ∈ (0, 1) and consider a symmetric MDC with a Ktuple of {R, R, ·· ·,R} as side quantizer rates. We show that if κ out of K descriptions are received, then the central distortion D (K,K) and the side distortions D (K,κ) satisfy lim R→ ∞ D(K,K) 2 2R[1+a(K−1)] = G(Λ)2 2h(f), lim R→ ∞ D(K,κ) 2 2R(1−a) = C(K, κ)G(SKL−L)2 2h(f),
JOINT OPTIMIZATION OF THE REDUNDANCY OF MULTIPLEDESCRIPTION CODERS FOR MULTICAST
"... We consider the optimization of multicast over packetswitched communication networks with a nonzero packetloss probability. For the system setup consisting of a number of multipledescription coders, we jointly optimize these coders. We propose an analytic solution, asymptotically optimal in the ..."
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We consider the optimization of multicast over packetswitched communication networks with a nonzero packetloss probability. For the system setup consisting of a number of multipledescription coders, we jointly optimize these coders. We propose an analytic solution, asymptotically optimal in the number of multipledescription coders. The analytic solution allows for fast system adaptation to changing network conditions. A locally optimal optimization algorithm that is useful when the number of multicast groups is small is derived. Simulations show that the utilization of the analytic solution incurs a low overhead on the performance when compared to the locally optimal solution, even for a small number of multipledescription coders. Index Terms — Multicast, multipledescription coding, optimization, packetloss