Fading observation alignment via feedback
IPSN '05 Proceedings of the 4th international symposium on Information processing in sensor networks
Foundations and Trends® in Networking
Convergence of a Class of Decentralized Beamforming Algorithms
SSP '07 Proceedings of the 2007 IEEE/SP 14th Workshop on Statistical Signal Processing
Finite state channels with time-invariant deterministic feedback
IEEE Transactions on Information Theory
Compound multiple-access channels with partial cooperation
IEEE Transactions on Information Theory
Distributed transmit beamforming: challenges and recent progress
IEEE Communications Magazine
Achieving the empirical capacity using feedback: memoryless additive models
IEEE Transactions on Information Theory
Zero-rate feedback can achieve the empirical capacity
IEEE Transactions on Information Theory
Feedback capacity of stationary Gaussian channels
IEEE Transactions on Information Theory
Linear Coherent Decentralized Estimation
IEEE Transactions on Signal Processing
On the Feasibility of Distributed Beamforming in Wireless Networks
IEEE Transactions on Wireless Communications
The quadratic Gaussian CEO problem
IEEE Transactions on Information Theory
The rate-distortion function for the quadratic Gaussian CEO problem
IEEE Transactions on Information Theory
The capacity of wireless networks
IEEE Transactions on Information Theory
The minimax distortion redundancy in noisy source coding
IEEE Transactions on Information Theory
Feedback capacity of finite-state machine channels
IEEE Transactions on Information Theory
IEEE Transactions on Information Theory
Variable length coding over an unknown channel
IEEE Transactions on Information Theory
Feedback capacity of the first-order moving average Gaussian channel
IEEE Transactions on Information Theory
IEEE Transactions on Information Theory
Joint Source–Channel Communication for Distributed Estimation in Sensor Networks
IEEE Transactions on Information Theory
Capacity of the Trapdoor Channel With Feedback
IEEE Transactions on Information Theory
Uncoded Transmission Is Exactly Optimal for a Simple Gaussian “Sensor” Network
IEEE Transactions on Information Theory
A history of transatlantic cables
IEEE Communications Magazine
Power, spatio-temporal bandwidth, and distortion in large sensor networks
IEEE Journal on Selected Areas in Communications
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Shannon's discovery of digital communication has shaped the architecture of virtually all communication systems in use today. The digital communication paradigm is built around the notion of bits and uses careful coding to deliver bits reliably end-to-end. It has been shown that this architectural principle can lead to a very significant performance penalty in wireless sensor networks. For a limited class of network scenarios, it was shown that optimal architectures are analog in nature, simple and scalable. In this paper, we show that more generally, simple analog architectures crucially depend on feedback to the sensors. Interesting questions then concern the amount of feedback needed and the resulting trade-off with performance. This paper provides rules-of-thumb for the selection of the number of feedback bits.