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Computation over Multiple-Access Channels (2007)
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| Venue: | IEEE TRANSACTIONS ON INFORMATION THEORY |
| Citations: | 137 - 24 self |
BibTeX
@ARTICLE{Nazer07computationover,
author = {Bobak Nazer and Michael Gastpar},
title = {Computation over Multiple-Access Channels},
journal = {IEEE TRANSACTIONS ON INFORMATION THEORY},
year = {2007},
volume = {53},
pages = {3498--3516}
}
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Abstract
The problem of reliably reconstructing a function of sources over a multiple-access channel is considered. It is shown that there is no source-channel separation theorem even when the individual sources are independent. Joint sourcechannel strategies are developed that are optimal when the structure of the channel probability transition matrix and the function are appropriately matched. Even when the channel and function are mismatched, these computation codes often outperform separation-based strategies. Achievable distortions are given for the distributed refinement of the sum of Gaussian sources over a Gaussian multiple-access channel with a joint source-channel lattice code. Finally, computation codes are used to determine the multicast capacity of finite field multiple-access networks, thus linking them to network coding.
Keyphrases
multiple-access channel computation code joint sourcechannel strategy individual source network coding joint source-channel lattice code achievable distortion channel probability transition matrix separation-based strategy gaussian multiple-access channel distributed refinement finite field multiple-access network source-channel separation theorem gaussian source
