TY - JOUR
T1 - Location estimation and detection in wireless sensor networks in the presence of fading
AU - Zhang, Xue
AU - Tepedelenlioglu, Cihan
AU - Banavar, Mahesh K.
AU - Spanias, Andreas
AU - Muniraju, Gowtham
N1 - Funding Information:
The work at Arizona State University was supported in part by the NSF ECCS award 1307982 .
Funding Information:
The work at Arizona State University was supported in part by the NSF ECCS award 1307982.
Funding Information:
Mahesh Banavar received a B.E. degree in telecommunications engineering from Visvesvaraya Technological University, Karnataka, India, in 2005 and M.S. and Ph.D. degrees, both in electrical engineering, from Arizona State University, Tempe, in 2007 and 2010, respectively. He is currently an Assistant Professor in the Department of Electrical and Computer Engineering at Clarkson University, Potsdam, NY. His interests include node localization, detection and estimation algorithms, and performance analysis of distributed sensor algorithms for wireless sensor networks. Dr. Banavar is a recipient of the Teaching Excellence Award from the Graduate and Professional Student Association at Arizona State University and the Outstanding Teaching Award from the Eta Kappa Nu chapter at Clarkson University. He is also a member of MENSA and the Eta Kappa Nu honor society.
Publisher Copyright:
© 2018 Elsevier B.V.
PY - 2019/2
Y1 - 2019/2
N2 - In this paper, localization using narrowband communication signals are considered in the presence of fading channels with time of arrival measurements. When narrowband signals are used for localization, due to existing hardware constraints, fading channels play a crucial role in localization accuracy. In a location estimation formulation, the Cramer–Rao lower bound for localization error is derived under different assumptions on fading coefficients. For the same level of localization accuracy, the loss in performance due to Rayleigh fading with known phase is shown to be about 5dB compared to the case with no fading. Unknown phase causes an additional 1dB loss. The maximum likelihood estimators are also derived. In an alternative distributed detection formulation, each anchor receives a noisy signal from a node with known location if the node is active. Each anchor makes a decision as to whether the node is active or not and transmits a bit to a fusion center once a decision is made. The fusion center combines all the decisions and uses a design parameter to make the final decision. We derive optimal thresholds and calculate the probabilities of false alarm and detection under different assumptions on the knowledge of channel information. Simulations corroborate our analytical results.
AB - In this paper, localization using narrowband communication signals are considered in the presence of fading channels with time of arrival measurements. When narrowband signals are used for localization, due to existing hardware constraints, fading channels play a crucial role in localization accuracy. In a location estimation formulation, the Cramer–Rao lower bound for localization error is derived under different assumptions on fading coefficients. For the same level of localization accuracy, the loss in performance due to Rayleigh fading with known phase is shown to be about 5dB compared to the case with no fading. Unknown phase causes an additional 1dB loss. The maximum likelihood estimators are also derived. In an alternative distributed detection formulation, each anchor receives a noisy signal from a node with known location if the node is active. Each anchor makes a decision as to whether the node is active or not and transmits a bit to a fusion center once a decision is made. The fusion center combines all the decisions and uses a design parameter to make the final decision. We derive optimal thresholds and calculate the probabilities of false alarm and detection under different assumptions on the knowledge of channel information. Simulations corroborate our analytical results.
KW - Distributed detection
KW - Fading channels
KW - Location estimation
KW - Narrowband signals
KW - Performance bounds
KW - Wireless sensor networks
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U2 - 10.1016/j.phycom.2018.10.010
DO - 10.1016/j.phycom.2018.10.010
M3 - Article
AN - SCOPUS:85057225341
SN - 1874-4907
VL - 32
SP - 62
EP - 74
JO - Physical Communication
JF - Physical Communication
ER -