The information-theoretic notion of energy efficiency is studied in the context of various joint source-channelcoding problems. The minimum transmission energy E(D) required to communicate a source over a noisy chann...
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The information-theoretic notion of energy efficiency is studied in the context of various joint source-channelcoding problems. The minimum transmission energy E(D) required to communicate a source over a noisy channel so that it can be reconstructed within a target distortion D is analyzed. Unlike the traditional joint source-channelcoding formalisms, no restrictions are imposed on the number of channel uses per source sample. For single-source memoryless point-to-point channels, E(D) is shown to be equal to the product of the minimum energy per bit E-bmin of the channel and the rate-distortion function R(D) of the source, regardless of whether channel output feedback is available at the transmitter. The primary focus is on Gaussian sources and channels affected by additive white Gaussian noise under quadratic distortion criteria, with or without perfect channel output feedback. In particular, for two correlated Gaussian sources communicated over a Gaussian multiple-access channel, inner and outer bounds on the energy-distortion region are obtained, which coincide in special cases. For symmetric channels, the difference between the upper and lower bounds on energy is shown to be at most a constant even when the lower bound goes to infinity as D -> 0. It is also shown that simple uncoded transmission schemes perform better than the separation-based schemes in many different regimes, both with and without feedback.
In this paper, we investigate the minimum energy of transmitting correlated sources over the Gaussian multiple-access channel. Compared to other works on joint source-channelcoding, we consider the fundamental proble...
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In this paper, we investigate the minimum energy of transmitting correlated sources over the Gaussian multiple-access channel. Compared to other works on joint source-channelcoding, we consider the fundamental problem of the minimum transmission energy, where the source and channel bandwidths are not naturally matched. Different models of correlated sources are studied. We first treat lossy transmission of Gaussian sources, including multiterminal sources and CEO sources. We then consider lossless transmission of correlated binary sources. In all cases, we lower bound the minimum energy using a cut-set argument that couples transmission energy and the distortions for the Gaussian cases (or source entropy for the discrete case). For the achievable schemes, separate source and channel coding and uncoded transmission are studied as benchmarks. In addition, we show that hybrid digital/analog transmission achieves the best known energy efficiency.
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