Lossy distributed source coding using graphs
IEEE Communications Letters
Error exponents for asymmetric two-user discrete memoryless source-channel coding systems
IEEE Transactions on Information Theory
Source and channel coding for correlated sources over multiuser channels
IEEE Transactions on Information Theory
A new achievable rate region for the discrete memoryless multiple-access channel with feedback
ISIT'09 Proceedings of the 2009 IEEE international conference on Symposium on Information Theory - Volume 4
A graph-based distributed reconstruction source coding with correlated messages
IEEE Communications Letters
BER reduction in signal receivers towards greening of digital communications
International Journal of Communication Networks and Distributed Systems
| Hi-index | 754.96 |
In this paper, we consider a graph-based framework for transmission of correlated sources over multiple-access channels. It is well known that the separation approach is not optimal for this multiuser communication. Our objective in this work is to reintroduce modularity in this problem using a graph-based discrete interface and to minimize the performance loss as compared to the optimal joint source-channel coding scheme. The proposed framework envisages a transmission systems with two modules: a source-coding module and a channel-coding module. In the former module, the correlated sources are encoded distributively into correlated messages whose correlation structure can be associated with a bipartite graph. These correlated messages are then encoded by using correlated codewords and are reliably transmitted over the multiple-access channel in the latter module. This leads to performance gains in terms of enlarging the class of correlated sources that can be reliably transmitted over a multiple-access channel as compared to the conventional separation approach. 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 multiuser 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 multiuser channel.