TY - JOUR
T1 - On the asymptotic efficiency of distributed estimation systems with constant modulus signals over multiple-access channels
AU - Tepedelenlioglu, Cihan
AU - Banavar, Mahesh K.
AU - Spanias, Andreas
N1 - Funding Information:
Manuscript received July 08, 2010; revised March 28, 2011; accepted June 06, 2011. This work was supported by the SenSIP Center, Arizona State University. Date of current version October 07, 2011.
PY - 2011/10
Y1 - 2011/10
N2 - A distributed estimation problem is considered with multiple-access channels between sensors and a fusion center. The sensors phase-modulate their noisy observations before transmitting them to the fusion center, where a signal parameter is estimated. The asymptotic efficiency of this estimator is then determined by using two inequalities that relate the Fisher information and the characteristic function. A necessary and sufficient condition for equality is found for the first time in the literature. The loss in efficiency of the distributed estimation scheme relative to the centralized approach is quantified for different sensing noise distributions. It is shown that this distributed estimation system does not incur an efficiency loss if and only if the sensing noise distribution is Gaussian.
AB - A distributed estimation problem is considered with multiple-access channels between sensors and a fusion center. The sensors phase-modulate their noisy observations before transmitting them to the fusion center, where a signal parameter is estimated. The asymptotic efficiency of this estimator is then determined by using two inequalities that relate the Fisher information and the characteristic function. A necessary and sufficient condition for equality is found for the first time in the literature. The loss in efficiency of the distributed estimation scheme relative to the centralized approach is quantified for different sensing noise distributions. It is shown that this distributed estimation system does not incur an efficiency loss if and only if the sensing noise distribution is Gaussian.
KW - Asymptotic efficiency
KW - Fisher information
KW - characteristic function
KW - distributed estimation
KW - wireless sensor network
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U2 - 10.1109/TIT.2011.2165806
DO - 10.1109/TIT.2011.2165806
M3 - Article
AN - SCOPUS:80053983904
SN - 0018-9448
VL - 57
SP - 7125
EP - 7130
JO - IEEE Transactions on Information Theory
JF - IEEE Transactions on Information Theory
IS - 10
M1 - 6034745
ER -