Elements of information theory
Elements of information theory
Reliability vs. efficiency in distributed source coding for field-gathering sensor networks
Proceedings of the 3rd international symposium on Information processing in sensor networks
Lossy network correlated data gathering with high-resolution coding
IEEE/ACM Transactions on Networking (TON) - Special issue on networking and information theory
Sensing workload scheduling in hierarchical sensor networks for data fusion applications
IWCMC '07 Proceedings of the 2007 international conference on Wireless communications and mobile computing
Source-channel communication in sensor networks
IPSN'03 Proceedings of the 2nd international conference on Information processing in sensor networks
Decentralized quickest change detection
IEEE Transactions on Information Theory
To code, or not to code: lossy source-channel communication revisited
IEEE Transactions on Information Theory
On the capacity of large Gaussian relay networks
IEEE Transactions on Information Theory
Networked Slepian-Wolf: theory, algorithms, and scaling laws
IEEE Transactions on Information Theory
Network information flow with correlated sources
IEEE Transactions on Information Theory
Multiterminal Source–Channel Communication Over an Orthogonal Multiple-Access Channel
IEEE Transactions on Information Theory
Towards the Optimal Amplify-and-Forward Cooperative Diversity Scheme
IEEE Transactions on Information Theory
A Case for Amplify–Forward Relaying in the Block-Fading Multiple-Access Channel
IEEE Transactions on Information Theory
IEEE Journal on Selected Areas in Communications
Power, spatio-temporal bandwidth, and distortion in large sensor networks
IEEE Journal on Selected Areas in Communications
On rate-constrained distributed estimation in unreliable sensor networks
IEEE Journal on Selected Areas in Communications
Distributed joint source-channel coding for functions over a multiple access channel
GLOBECOM'09 Proceedings of the 28th IEEE conference on Global telecommunications
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We address the problem of estimating a random field via a wireless sensor network. We use a Multiple Access Channel (MAC) as the basic building block for such a network. For Gaussian sources over Gaussian MACs, we show that Amplify and Forward scheme (AF) performs well in such sensor network scenarios where the battery power is at a premium. We then extend this result to the hierarchical network scenario and show that it can perform favourably to the Slepian-Wolf based source coding and independent channel coding scheme. Since AF is simple and scalable, a good performance makes it an attractive scheme.