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Decision fusion for composite hypothesis testing in wireless sensor networks over a shared and noisy collision channel

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  • Seksan Laitrakun

Abstract

We consider the composite hypothesis testing problem of time-bandwidth-constrained distributed detection. In this scenario, the probability distribution of the observed signal when the event of interest is happening is unknown. In addition, local decisions are censored and only those uncensored local decisions will be sent to the fusion center over a shared and noisy collision channel. The fusion center also has a limited time duration to collect transmitted decisions and make a final decision. Two types of medium access control that the sensor nodes apply to send their decisions are investigated: time division multiple access and slotted-Aloha. Unlike using the time division multiple access protocol, the slotted-Aloha-based distributed detection will experience packet collisions. However, in this article, since only uncensored decisions are sent, packet collisions are informative. We derive fusion rules according to generalized likelihood ratio test, Rao test, and Wald test for both the time division multiple access–based distributed detection and the slotted-Aloha-based distributed detection. We see that the fusion rules for the slotted-Aloha-based distributed detection here also exploit packet collisions in the final decision-making. In addition, the asymptotic performances and energy consumption of both schemes are analyzed. Extensive simulation and numerical results are provided to compare the performances of these two schemes. We show that, for a given time delay, the slotted-Aloha-based distributed detection can outperform the time division multiple access–based distributed detection by increasing the number of sensor nodes which results in higher energy consumption.

Suggested Citation

  • Seksan Laitrakun, 2020. "Decision fusion for composite hypothesis testing in wireless sensor networks over a shared and noisy collision channel," International Journal of Distributed Sensor Networks, , vol. 16(7), pages 15501477209, July.
  • Handle: RePEc:sae:intdis:v:16:y:2020:i:7:p:1550147720940204
    DOI: 10.1177/1550147720940204
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