Channel Optimized Distributed Multiple Description Coding

In this paper, channel optimized distributed multiple description vector quantization (CDMD) schemes are presented for distributed source coding in symmetric and asymmetric settings. The CDMD encoder is designed using a deterministic annealing approach over noisy channels with packet loss. A minimum mean squared error asymmetric CDMD decoder is proposed for effective reconstruction of a source, utilizing the side information (SI) and its corresponding received descriptions. The proposed iterative symmetric CDMD decoder jointly reconstructs the symbols of multiple correlated sources. Two types of symmetric CDMD decoders, namely the estimated-SI and the soft-SI decoders, are presented which respectively exploit the reconstructed symbols and a posteriori probabilities of other sources as SI in iterations. In a multiple source CDMD setting, for reconstruction of a source, three methods are proposed to select another source as its SI during the decoding. The methods operate based on minimum physical distance (in a wireless sensor network setting), maximum mutual information and minimum end-to-end distortion. The performance of the proposed systems and algorithms are evaluated and compared in detail.Comment: Submitted to IEEE Transaction on Signal Processin

Multiple-Description Coding by Dithered Delta-Sigma Quantization

We address the connection between the multiple-description (MD) problem and Delta-Sigma quantization. The inherent redundancy due to oversampling in Delta-Sigma quantization, and the simple linear-additive noise model resulting from dithered lattice quantization, allow us to construct a symmetric and time-invariant 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 Delta-Sigma quantization scheme approaches the symmetric two-channel MD rate-distortion function for a memoryless Gaussian source and MSE fidelity criterion, at any side-to-central distortion ratio and any resolution. In the optimal scheme, the infinite-order noise shaping filter must be minimum phase and have a piece-wise 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.Comment: Revised, restructured, significantly shortened and minor typos has been fixed. Accepted for publication in the IEEE Transactions on Information Theor

Asymptotic Estimates in Information Theory with Non-Vanishing Error Probabilities

This monograph presents a unified treatment of single- and multi-user problems in Shannon's information theory where we depart from the requirement that the error probability decays asymptotically in the blocklength. Instead, the error probabilities for various problems are bounded above by a non-vanishing constant and the spotlight is shone on achievable coding rates as functions of the growing blocklengths. This represents the study of asymptotic estimates with non-vanishing error probabilities. In Part I, after reviewing the fundamentals of information theory, we discuss Strassen's seminal result for binary hypothesis testing where the type-I error probability is non-vanishing and the rate of decay of the type-II error probability with growing number of independent observations is characterized. In Part II, we use this basic hypothesis testing result to develop second- and sometimes, even third-order asymptotic expansions for point-to-point communication. Finally in Part III, we consider network information theory problems for which the second-order asymptotics are known. These problems include some classes of channels with random state, the multiple-encoder distributed lossless source coding (Slepian-Wolf) problem and special cases of the Gaussian interference and multiple-access channels. Finally, we discuss avenues for further research.Comment: Further comments welcom

Distributed Joint Source-Channel Coding in Wireless Sensor Networks

Considering the fact that sensors are energy-limited and the wireless channel conditions in wireless sensor networks, there is an urgent need for a low-complexity coding method with high compression ratio and noise-resisted features. This paper reviews the progress made in distributed joint source-channel coding which can address this issue. The main existing deployments, from the theory to practice, of distributed joint source-channel coding over the independent channels, the multiple access channels and the broadcast channels are introduced, respectively. To this end, we also present a practical scheme for compressing multiple correlated sources over the independent channels. The simulation results demonstrate the desired efficiency

Gains from international monetary policy coordination: does it pay to be different?

This paper presents a new argument for international monetary policy coordination based on considerations of structural asymmetries across countries. In a two-country world with a traded and a non-traded sector in each country, optimal independent monetary policy cannot replicate the natural-rate allocations. There are potential welfare gains from coordination since the planner under a cooperating regime internalizes a terms-of-trade externality that independent central banks tend to overlook. Yet, with symmetric structures across countries, the gains are quantitatively small. If the size of the traded sector differs across countries, the gains can be sizable and increase with the degree of asymmetry. The planner's optimal policy not only internalizes the terms-of-trade externality, it also creates a terms-of-trade bias in favor the country with a larger traded sector. Further, the planner tries to balance the terms-of-trade bias against the need to stabilize fluctuations in the terms-of-trade gap. JEL Classification: E52, F41, F42Asymmetric Structures, International Policy Coordination, optimal monetary policy, Terms-of-Trade Bias