TY - GEN
T1 - Decision fusion in a wireless sensor network with a random number of sensors
AU - Niu, Ruixin
AU - Varshney, Pramod K.
PY - 2005
Y1 - 2005
N2 - For a wireless sensor network (WSN) with a random number of sensors, a decision fusion rule that uses the total number of detections reported by local sensors for hypothesis testing, is proposed. It is assumed that the number of sensors follows a Poisson distribution and the locations of sensors follow a uniform distribution within the region of interest (ROI). Both analytical and simulation results for the system level detection performance are provided. This fusion rule can achieve a very good system level detection performance even at very low signal to noise ratio (SNR), if the average number of sensors is sufficiently large. In addition, the problem of choosing an optimum local sensor level threshold is investigated for various system parameters.
AB - For a wireless sensor network (WSN) with a random number of sensors, a decision fusion rule that uses the total number of detections reported by local sensors for hypothesis testing, is proposed. It is assumed that the number of sensors follows a Poisson distribution and the locations of sensors follow a uniform distribution within the region of interest (ROI). Both analytical and simulation results for the system level detection performance are provided. This fusion rule can achieve a very good system level detection performance even at very low signal to noise ratio (SNR), if the average number of sensors is sufficiently large. In addition, the problem of choosing an optimum local sensor level threshold is investigated for various system parameters.
UR - http://www.scopus.com/inward/record.url?scp=33646798803&partnerID=8YFLogxK
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U2 - 10.1109/ICASSP.2005.1416145
DO - 10.1109/ICASSP.2005.1416145
M3 - Conference contribution
AN - SCOPUS:33646798803
SN - 0780388747
SN - 9780780388741
T3 - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
SP - 861
EP - 864
BT - 2005 IEEE ICASSP '05 - Proc. - Design and Implementation of Signal Proces.Syst.,Indust. Technol. Track,Machine Learning for Signal Proces. Signal Proces. Education, Spec. Sessions
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2005 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP '05
Y2 - 18 March 2005 through 23 March 2005
ER -