11,275 research outputs found
Computing sum of sources over an arbitrary multiple access channel
The problem of computing sum of sources over a multiple access channel (MAC)
is considered. Building on the technique of linear computation coding (LCC)
proposed by Nazer and Gastpar [2007], we employ the ensemble of nested coset
codes to derive a new set of sufficient conditions for computing the sum of
sources over an \textit{arbitrary} MAC. The optimality of nested coset codes
[Padakandla, Pradhan 2011] enables this technique outperform LCC even for
linear MAC with a structural match. Examples of nonadditive MAC for which the
technique proposed herein outperforms separation and systematic based
computation are also presented. Finally, this technique is enhanced by
incorporating separation based strategy, leading to a new set of sufficient
conditions for computing the sum over a MAC.Comment: Contains proof of the main theorem and a few minor corrections.
Contents of this article have been accepted for presentation at ISIT201
A Graph-based Framework for Transmission of Correlated Sources over Broadcast Channels
In this paper we consider the communication problem that involves
transmission of correlated sources over broadcast channels. We consider a
graph-based framework for this information transmission problem. The system
involves a source coding module and a channel coding module. In the source
coding module, the sources are efficiently mapped into a nearly semi-regular
bipartite graph, and in the channel coding module, the edges of this graph are
reliably transmitted over a broadcast channel. We consider nearly semi-regular
bipartite graphs as discrete interface between source coding and channel coding
in this multiterminal setting. We provide an information-theoretic
characterization of (1) the rate of exponential growth (as a function of the
number of channel uses) of the size of the bipartite graphs whose edges can be
reliably transmitted over a broadcast channel and (2) the rate of exponential
growth (as a function of the number of source samples) of the size of the
bipartite graphs which can reliably represent a pair of correlated sources to
be transmitted over a broadcast channel.Comment: 36 pages, 9 figure
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