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It is well known that independent (separate) encoding of $K$ correlated sources may incur some rate loss compared to joint encoding, even if the decoding is done jointly. This loss is particularly evident in the multiple descriptions problem, where it is the same source that is encoded in each description. We observe that under mild conditions about the source and distortion measure, the sum-rate of $K$ separately encoded individually good descriptions tends to the rate-distortion function of the joint decoder in the limit of vanishing small coding rates of the descriptions. Moreover, we then propose to successively encode the source into $K$ independent descriptions in each round in order to achieve a final distortion $D$ after $M$ rounds. We provide two examples – a Gaussian source with mean-squared error and an exponential source with one-sided error – for which the excess rate vanishes in the limit as the number of rounds $M$ goes to infinity, for any fixed $D$ and $K$. This result has an interesting interpretation for a multi-round variant of the multiple descriptions problem, where after each round the encoder gets a (block) feedback regarding which of the descriptions arrived: In the limit as the number of rounds $M$ goes to infinity (i.e., many incremental rounds), the total rate of received descriptions approaches the rate-distortion function. We provide theoretical and experimental evidence showing that this phenomenon is in fact more general than in the two examples above. [ABSTRACT FROM AUTHOR]

We present a closed-form expression for the minimal delay that is achievable in a setting that combines a buffer and an erasure code, used to mitigate the packet delay variance. The erasure code is modeled according to the recent information-theoretic results on finite block length codes. Evaluations reveal that accurate knowledge of the network parameters is essential for optimal operation. Moreover, it is shown that, when the network packet delay variance is large, the buffer delay becomes negligible. Therefore, in this case, the delay budget should be spent mainly on the erasure code. [ABSTRACT FROM PUBLISHER]

It is well known that Shannon’s rate-distortion function (RDF) in the colored quadratic Gaussian (QG) case can be parametrized via a single Lagrangian variable (the water level in the reverse water filling solution). In this paper, we show that the symmetric colored QG multiple description (MD) RDF in the case of two descriptions can be parametrized in the spectral domain via two Lagrangian variables, which control the tradeoff between the side distortion, the central distortion, and the coding rate. This spectral-domain analysis is complemented by a time-domain scheme-design approach: we show that the symmetric colored QG MD RDF can be achieved by combining ideas of delta–sigma modulation and differential pulse-code modulation. In particular, two source prediction loops, one for each description, are embedded within a common noise-shaping loop, whose parameters are explicitly found from the spectral-domain characterization. [ABSTRACT FROM AUTHOR]

We analyze a class of rateless codes, called Luby transform (LT) codes with unequal error protection (UEP). We show that while these codes successfully provide UEP, there is a significant price in terms of redundancy in the lower prioritized segments. We propose a modification with a single intermediate feedback message. Our analysis shows a dramatic improvement on the decoding performance of the lower prioritized segment. [ABSTRACT FROM PUBLISHER]

In this paper we propose a new design of LT codes, which decreases the amount of necessary overhead in comparison to existing designs. The design focuses on a parameter of the LT decoding process called the ripple size. This parameter was also a key element in the design proposed in the original work by Luby. Specifically, Luby argued that an LT code should provide a constant ripple size during decoding. In this work we show that the ripple size should decrease during decoding, in order to reduce the necessary overhead. Initially we motivate this claim by analytical results related to the redundancy within an LT code. We then propose a new design procedure, which can provide any desired achievable decreasing ripple size. The new design procedure is evaluated and compared to the current state of the art through simulations. This reveals a significant increase in performance with respect to both average overhead and error probability at any fixed overhead. [ABSTRACT FROM AUTHOR]

A novel scheme for perceptual coding of audio for robust and real-time communication is designed and analyzed. As an alternative to PCM, DPCM, and more general noise-shaping converters, we propose to use psychoacoustically optimized noise-shaping quantizers based on the moving-horizon principle. In moving-horizon quantization, a few samples look-ahead is allowed at the encoder, which makes it possible to better shape the quantization noise and thereby reduce the resulting distortion over what is possible with conventional noise-shaping techniques. It is first shown that significant gains over linear PCM can be obtained without introducing a delay and without requiring postprocessing at the decoder, i.e., the encoded samples can be stored as, e.g., 16-bit linear PCM on CD-ROMs, and played out on standards-compliant CD players. We then show that multiple-description coding can be combined with moving-horizon quantization in order to combat possible erasures on the wireless link without introducing additional delays. [ABSTRACT FROM AUTHOR]

This paper is about the design and analysis of an index-assignment (IA)-based multiple-description coding scheme for the n-channel asymmetric case. We use entropy constrained lattice vector quantization and restrict attention to simple reconstruction functions, which are given by the inverse IA function when all descriptions are received or otherwise by a weighted average of the received descriptions. We consider smooth sources with finite differential entropy rate and MSE fidelity criterion. As in previous designs, our construction is based on nested lattices which are combined through a single IA function. The results are exact under high-resolution conditions and asymptotically as the nesting ratios of the lattices approach infinity. For any n, the design is asymptotically optimal within the class of IA-based schemes. Moreover, in the case of two descriptions and finite lattice vector dimensions greater than one, the performance is strictly better than that of existing designs. In the case of three descriptions, we show that in the limit of large lattice vector dimensions, points on the inner bound of Pradhan can be achieved. Furthermore, for three descriptions and finite lattice vector dimensions, we show that the IA-based approach yields, in the symmetric case, a smaller rate loss than the recently proposed source-splitting approach. [ABSTRACT FROM AUTHOR]

We study state estimation via wireless sensors over fading channels. Packet loss probabilities depend upon time-varying channel gains, packet lengths and transmission power levels of the sensors. Measurements are coded into packets by using either independent coding or distributed zero-error coding. At the gateway, a time-varying Kalman filter uses the received packets to provide the state estimates. To trade sensor energy expenditure for state estimation accuracy, we develop a predictive control algorithm which, in an online fashion, determines the transmission power levels and codebooks to be used by the sensors. To further conserve sensor energy, the controller is located at the gateway and sends coarsely quantized power increment commands, only whenever deemed necessary. Simulations based on real channel measurements illustrate that the proposed method gives excellent results. [ABSTRACT FROM PUBLISHER]

This paper studies the tight rate-distortion bound for L-channel symmetric multiple-description coding of a scalar Gaussian source with two levels of receivers. Each of the first-level receivers obtains κ of the L descriptions (κ < L). The second-level receiver obtains all L descriptions. We find that if the central distortion (corresponding to the second-level receiver) is much smaller than the side distortion (corresponding to the first-level receivers), the product of a function of the side distortions and the central distortion is asymptotically independent of the redundancy between the descriptions. Using this property, we analyze the asymptotic behavior of a practical multiple-description lattice vector quantizer (MDLVQ). Our analysis includes the treatment of the MDLVQ system from a new geometric viewpoint, which results in an expression for the side distortions using the normalized second moment of a sphere of higher dimensionality than the quantization space. The expression of the distortion product derived from the lower bound is then applied as a criterion to assess the performance loss of the considered MDLVQ system. In principle, the efficiency of other practical MD systems can also be evaluated using the derived distortion product. [ABSTRACT FROM PUBLISHER]