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Jonathan E. W. Huffmann

Publications and source records attributed to Jonathan E. W. Huffmann.

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Deterministic Identification over Additive Gaussian Channels

Modern communication systems impose strict demands on data rate, reliability, and power efficiency. In this context, emerging communication paradigms such as identification via channels have become an important topic in post-Shannon information theory, offering the potential for substantially higher identification rates than in conventional channel coding.Deterministic identification is particularly interesting for specialized communication scenarios because it provides a balance between implementation complexity and the communication gains due to higher identification rates. It is therefore a promising communication scheme for future communication systems, including molecular communication systems. Additive Gaussian channels, particularly the additive white Gaussian channel, are among the most important channel models for analyzing the performance of communication systems in information and communication theory. This importance stems from both their mathematical tractability and their ubiquitous appearance in practical applications. To date the deterministic identification capacity for additive Gaussian channels remains unknown even for the simplest case of the additive white Gaussian channel. In this paper, we establish tight bounds on the deterministic identification capacity of additive Gaussian channels by introducing a new perspective on deterministic identification. To this end, we apply results from lattice theory to obtain new capacity results.

cs.IT

Computability of the Optimizer for Rate Distortion Functions

Rate distortion theory treats the problem of encoding a source with minimum codebook size while at the same time allowing for a certain amount of errors in the reconstruction measured by a fidelity criterion and distortion level. Similar to the channel coding problem the optimal rate of the codebook with respect to the blocklength is given by a convex optimization problem involving information theoretic quantities like mutual information. The value of the rate in dependence of the distortion level as well as the optimizer used in the codebook construction are of theoretical and practical importance in communication and information theory. In this paper the behavior of the rate distortion function regarding the computability of the optimizing test channel is investigated. We find that comparable with known results about the optimizer for other information theoretic problems a similar result is found to be true also regarding the computability of the optimizer for rate distortion functions. It turns out that while the rate distortion function is usually computable the optimizer for this problem is in general non-computable even for simple distortion measures.

cs.IT