Average Error Probability in Wireless Sensor Networks With Imperfect Sensing and Communication for Different Decision Rules

This paper presents a framework to evaluate the probability that a decision error event occurs in wireless sensor networks, including sensing and communication errors. We consider a scenario where sensors need to identify whether a given event has occurred based on its periodic, noisy, and observati...

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Bibliographic Details
Published in:IEEE sensors journal 2016-05, Vol.16 (10), p.3948-3957
Main Authors: Nardelli, Pedro Henrique Juliano, Ramezanipour, Iran, Alves, Hirley, de Lima, Carlos H. M., Latva-Aho, Matti
Format: Article
Language:English
Subjects:
Data fusion
distributed detection
Error analysis
Error probability
Estimation
Probability
Sensor fusion
Sensor phenomena and characterization
Sensor systems
Sensors
Wireless sensor networks
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Summary:This paper presents a framework to evaluate the probability that a decision error event occurs in wireless sensor networks, including sensing and communication errors. We consider a scenario where sensors need to identify whether a given event has occurred based on its periodic, noisy, and observations of a given signal. Such information about the signal needs to be sent to a fusion center that decides about the actual state at that specific observation time. The communication links-single-or multi-hop-are modeled as binary symmetric channels, which may have different error probabilities. The decision at the fusion center is based on OR, AND, K-OUT-OF-N, and MAJORITY Boolean operations on the received signals associated to individual sensor observations. We derive closed-form equations for the average decision error probability as a function of the system parameters (e.g., number of sensors and hops) and the input signal characterization. Our analyses show the best decision rule is closely related to the frequency that the observed events occur and the number of sensors. In our numerical example, we show that the AND rule outperforms MAJORITY if such an event is rare and there is only a handful number of sensors. Conversely, if there are a large number of sensors or more evenly distributed event occurrences, the MAJORITY is the best choice. We further show that, while the error probability using the MAJORITY rule asymptotically goes to 0 with increasing number of sensors, it is also more susceptible to higher channel error probabilities.
ISSN:1530-437X
1558-1748
DOI:10.1109/JSEN.2016.2536148