We present and analyze a joint source-channel coding strategy for the
transmission of a Gaussian source across a Gaussian channel in n channel uses
per source symbol. Among all such strategies, our scheme has the following
properties: i) the resulting mean-squared error scales optimally with the
signal-to-noise ratio, and ii) the scheme is easy to implement and the incurred
delay is minimal, in the sense that a single source symbol is encoded at a
time.Comment: 5 pages, 1 figure, final version accepted at IEEE Globecom 2009
(Communication Theory Symposium
Although more and more data is collected automatically, many interfaces still require manual input. When we, for example, enter our daily calorie intake or calculate our ecological footprint, we often have to guess the weight of the food or what distance we have covered with our car. In this paper, we propose a solution to overcome the problem of forcing users to enter a single value when they are unsure about the actual input. On the basis of a slider, we designed four input controls which allow the input of uncertain data in the form of probability distribution functions. To evaluate our input controls, we conducted two studies collecting subjective and objective feedback. Based on the evaluation, we derived implications for their usage. We additionally provide an open-source toolkit with the evaluated input controls that can be included in web applications and customized for different contexts and tasks.
We consider source coding with a fidelity criterion, channel coding with a channel input constraint, and the combined problem of reproducing a source across a noisy channel. All three cases face a similar tradeoff between resource and performance, and the operating point with the highest performance per resource is of particular interest. In the case of channel coding, channel input cost is traded for rate, and the optimal tradeoff corresponds to the capacity per unit cost. We define equivalent notions for the other two cases and show how they relate. For each case we give necessary and sufficient conditions for the optimal tradeoff to be achieved.
Abstract-An analog source is to be transmitted across a Gaussian channel in more than one channel use per source symbol. This paper derives a lower bound on the asymptotic mean squared error for a strategy that consists of repeatedly quantizing the source, transmitting the quantizer outputs in the first channel uses, and sending the remaining quantization error uncoded in the last channel use. The bound coincides with the performance achieved by a suboptimal decoder studied by the authors in a previous paper, thereby establishing that the bound is tight.
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