How to distribute sensors in a random field?
Proceedings of the 3rd international symposium on Information processing in sensor networks
Power-bandwidth-distortion scaling laws for sensor networks
Proceedings of the 3rd international symposium on Information processing in sensor networks
Robustness vs. efficiency in sensor networks
IPSN '05 Proceedings of the 4th international symposium on Information processing in sensor networks
Fading observation alignment via feedback
IPSN '05 Proceedings of the 4th international symposium on Information processing in sensor networks
IWCMC '07 Proceedings of the 2007 international conference on Wireless communications and mobile computing
An energy-efficient adaptive DSC scheme for wireless sensor networks
Signal Processing
Distortion-rate bounds for distributed estimation using wireless sensor networks
EURASIP Journal on Advances in Signal Processing
Cores of cooperative games in information theory
EURASIP Journal on Wireless Communications and Networking - Theory and Applications in Multiuser/Multiterminal Communications
Optimal rate allocation in successively structured Gaussian CEO problem
IEEE Transactions on Wireless Communications
IEEE Transactions on Image Processing
Distributed MIMO receiver: achievable rates and upper bounds
IEEE Transactions on Information Theory
On the minimum sum rate of Gaussian multiterminal source coding: new proofs
ISIT'09 Proceedings of the 2009 IEEE international conference on Symposium on Information Theory - Volume 3
The quadratic Gaussian CEO problem with Byzantine agents
ISIT'09 Proceedings of the 2009 IEEE international conference on Symposium on Information Theory - Volume 2
The entropy power of a sum is fractionally superadditive
ISIT'09 Proceedings of the 2009 IEEE international conference on Symposium on Information Theory - Volume 1
A vector generalization of Costa entropy-power inequality and applications
ISIT'09 Proceedings of the 2009 IEEE international conference on Symposium on Information Theory - Volume 1
Distributed MIMO systems for nomadic applications over a symmetric interference channel
IEEE Transactions on Information Theory
IEEE Transactions on Information Theory
Source-channel communication in sensor networks
IPSN'03 Proceedings of the 2nd international conference on Information processing in sensor networks
On rate-constrained estimation in unreliable sensor networks
IPSN'03 Proceedings of the 2nd international conference on Information processing in sensor networks
A vector generalization of costa's entropy-power inequality with applications
IEEE Transactions on Information Theory
The Gaussian many-help-one distributed source coding problem
IEEE Transactions on Information Theory
Sending a bivariate Gaussian over a Gaussian MAC
IEEE Transactions on Information Theory
Brief paper: Min-max optimal data encoding and fusion in sensor networks
Automatica (Journal of IFAC)
A little feedback can simplify sensor network cooperation
IEEE Journal on Selected Areas in Communications - Special issue on simple wireless sensor networking solutions
On the sum rate of Gaussian multiterminal source coding: new proofs and results
IEEE Transactions on Information Theory
ACM Transactions on Sensor Networks (TOSN)
Hi-index | 755.26 |
A new multiterminal source coding problem called the CEO problem was presented and investigated by Berger, Zhang, and Viswanathan. Recently, Viswanathan and Berger have investigated an extension of the CEO problem to Gaussian sources and call it the quadratic Gaussian CEO problem. They considered this problem from a statistical viewpoint, deriving some interesting results. In this paper, we consider the quadratic Gaussian CEO problem from a standpoint of multiterminal rate-distortion theory. We regard the CEO problem as a certain multiterminal remote source coding problem with infinitely many separate encoders whose observations are conditionally independent if the remote source is given. This viewpoint leads us to a complete solution to the problem. We determine the tradeoff between the total amount of rate and squared distortion, deriving an explicit formula of the rate-distortion function. The derived function has the form of a sum of two nonnegative functions. One is a classical rate-distortion function for single Gaussian source and the other is a new rate-distortion function which dominates the performance of the system for a relatively small distortion. It follows immediately from our result that the conjecture of Viswanathan and Berger on the asymptotic behavior of minimum squared distortion for large rates is true