Title
Optimal Training and Data Power Allocation in Distributed Detection With Inhomogeneous Sensors
Abbreviated Journal Title
IEEE Signal Process. Lett.
Keywords
Channel estimation; deflection coefficient; distributed detection; optimal power allocation; COGNITIVE RADIO; NETWORKS; CHANNELS; FUSION; Engineering, Electrical & Electronic
Abstract
We consider a binary distributed detection problem in a wireless sensor network with inhomogeneous sensors, in which sensors send their binary phase shift keying (BPSK) modulated decisions to the fusion center (FC) over orthogonal channels that are subject to pathloss, Rayleigh fading, and Gaussian noise. Assuming training based channel estimation, we consider a linear fusion rule which employs imperfect channel state information (CSI) to form the global decision at the FC. Under the constraint that the total transmit power of training and decision symbols at each sensor is fixed, we analytically derive the optimal power allocation between training and data at each sensor such that the deflection coefficient at the FC is maximized. Our analysis shows that the proposed optimal power allocation scheme is a function of signal-to-noise (SNR) and local detection indices, and at high SNR regime, the proposed scheme outperforms the uniform power allocation.
Journal Title
Ieee Signal Processing Letters
Volume
20
Issue/Number
4
Publication Date
1-1-2013
Document Type
Article
Language
English
First Page
339
Last Page
342
WOS Identifier
ISSN
1070-9908
Recommended Citation
"Optimal Training and Data Power Allocation in Distributed Detection With Inhomogeneous Sensors" (2013). Faculty Bibliography 2010s. 3592.
https://stars.library.ucf.edu/facultybib2010/3592
Comments
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