DocumentCode :
230807
Title :
Optimal observations transmission for distributed estimation under energy constraint
Author :
Alkhweldi, Marwan
Author_Institution :
Lane Dept. of Comput. Sci. & Electr. Eng., West Virginia Univ., Morgantown, WV, USA
fYear :
2014
fDate :
9-12 Dec. 2014
Firstpage :
1
Lastpage :
6
Abstract :
This paper studies the problem of distributed parameter estimation in wireless sensor network under energy constraints. Optimization formulas that find the optimal sensors´ observations transmission that guarantee the best estimation performance from the available energy are derived. The network consists of sensors that are deployed over an area at random. Sensors´ observations are noisy measurements of an underlying field. Sensors have limited energy for the transmission process. Each sensor processes its observation prior to transmitting it to a fusion center, where a field parameter vector is estimated. Transmission channels between the sensors and the fusion center are assumed to be noisy parallel channels. The sensors´ locations, the noise probability density function, and the field characteristic function are assumed to be known at the fusion center. Simulation results which support the optimization formulas are shown.
Keywords :
distributed algorithms; optimisation; parameter estimation; probability; sensor placement; wireless channels; wireless sensor networks; distributed parameter estimation; energy constraint; field parameter vector estimation; fusion center; noise probability density function; noisy parallel channels; optimal sensor observations transmission; sensor location; transmission channels; wireless sensor network; Estimation; Optimization; Quantization (signal); Sensor phenomena and characterization; Vectors; Wireless sensor networks; Wireless sensor network; distributed parameter estimation; energy constraint; maximum-likelihood estimation; mean squared error;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence for Communication Systems and Networks (CIComms), 2014 IEEE Symposium on
Conference_Location :
Orlando, FL
Type :
conf
DOI :
10.1109/CICommS.2014.7014642
Filename :
7014642
Link To Document :
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