Title
Optimal Training And Data Power Allocation In Distributed Detection With Inhomogeneous Sensors
Keywords
Channel estimation; deflection coefficient; distributed detection; optimal power allocation
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. © 1994-2012 IEEE.
Publication Date
3-19-2013
Publication Title
IEEE Signal Processing Letters
Volume
20
Issue
4
Number of Pages
339-342
Document Type
Article
Personal Identifier
scopus
DOI Link
https://doi.org/10.1109/LSP.2013.2246514
Copyright Status
Unknown
Socpus ID
84874995258 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/84874995258
STARS Citation
Ahmadi, Hamid R. and Vosoughi, Azadeh, "Optimal Training And Data Power Allocation In Distributed Detection With Inhomogeneous Sensors" (2013). Scopus Export 2010-2014. 6776.
https://stars.library.ucf.edu/scopus2010/6776