On linear coherent estimation with spatial collaboration

@article{Kar2012OnLC,
  title={On linear coherent estimation with spatial collaboration},
  author={Swarnendu Kar and Pramod K. Varshney},
  journal={2012 IEEE International Symposium on Information Theory Proceedings},
  year={2012},
  pages={1448-1452}
}
  • Swarnendu KarP. Varshney
  • Published 15 May 2012
  • Computer Science
  • 2012 IEEE International Symposium on Information Theory Proceedings
We consider a power-constrained sensor network, consisting of multiple sensor nodes and a fusion center (FC), that is deployed for the purpose of estimating a common random parameter of interest. In contrast to the distributed framework, the sensor nodes are allowed to update their individual observations by (linearly) combining observations from neighboring nodes. The updated observations are communicated to the FC using an analog amplify-and-forward modulation scheme and through a coherent… 
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References

SHOWING 1-10 OF 34 REFERENCES

Power constrained distributed estimation with cluster-based sensor collaboration

It is shown that the optimum collaboration strategy is to compress the data into one local message which, depending on the channel characteristics, is transmitted using one or multiple available channels to the FC.

Linear Coherent Decentralized Estimation

It is shown that when the MAC between sensors and the fusion center is noiseless, the resulting problem has a closed-form solution (which is in sharp contrast to the orthogonal MAC case), while in the noisy MAC case the problem can be efficiently solved by semidefinite programming (SDP).

Spatial whitening framework for distributed estimation

  • Swarnendu KarP. VarshneyHao Chen
  • Computer Science
    2011 4th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP)
  • 2011
An adjacency-based spatial whitening scheme, where each sensor exchanges its observation with their neighbors prior to encoding their own private information and transmitting it to the fusion center, is proposed.

Estimation Diversity and Energy Efficiency in Distributed Sensing

It is shown that by turning off bad sensors, i.e., sensors with bad channels and bad observation quality, adaptive power gain can be achieved without sacrificing diversity gain, and some related energy efficiency issues in sensor networks are discussed.

Universal decentralized estimation in a bandwidth constrained sensor network

  • Z. Luo
  • Computer Science
    IEEE Transactions on Information Theory
  • 2005
This correspondence investigates optimal local estimation and final fusion schemes under the constraint that the communication from each sensor to the fusion center must be a one-bit message.

Distributed MMSE Relay Strategies for Wireless Sensor Networks

This paper proposes and study two-hop multisensor relay strategies that achieve minimum mean-square-error (MSE) performance subject to either local or global power constraints.

Distributed Estimation in Energy-Constrained Wireless Sensor Networks

The theoretical energy-distortion performance bound for distributed estimation of a noise-corrupted deterministic parameter in energy-constrained wireless sensor networks is addressed and it is shown that the proposed algorithm is quasi-optimal within a factor 2 of the theoretical lower bound.

Collaborative-Relay Beamforming With Perfect CSI: Optimum and Distributed Implementation

This letter shows that the optimal collaborative-relay beamforming (CRB) solution achieves the full diversity of a MISO antenna system and develops a distributed algorithm that allows each individual relay to learn its own weight, based on the Karush-Kuhn-Tucker (KKT) analysis.

Cooperative Transmission for Relay Networks Based on Second-Order Statistics of Channel State Information

It is shown that the semidefinite programming (SDP) relaxation of the original problem always has a rank one solution, and hence the original issue is equivalent to finding theRank one solution of the SDP problem.

Distributed Beamforming for Relay Networks Based on Second-Order Statistics of the Channel State Information

It is shown that using semidefinite relaxation, the problem of distributed beamforming is considered for a wireless network which consists of a transmitter, a receiver, and relay nodes and is efficiently solved using interior point methods.