Quantized fusion rules for energy-based distributed detection in wireless sensor networks

Nurellari, Edmond, Aldalahmeh, Sami, Ghogho, Mounir and McLernon, Des (2014) Quantized fusion rules for energy-based distributed detection in wireless sensor networks. In: Sensor Signal Processing for Defence (SSPD), 2014, 8 - 9 September 2014, Edinburgh.

Full content URL: http://dx.doi.org/10.1109/SSPD.2014.6943313

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Item Type:Conference or Workshop contribution (Presentation)
Item Status:Live Archive


We consider the problem of soft decision fusion in a bandwidth-constrained wireless sensor network (WSN). The WSN is tasked with the detection of an intruder transmitting an unknown signal over a fading channel. A binary hypothesis testing is performed using the soft decision of the sensor nodes (SNs). Using the likelihood ratio test, the optimal soft fusion rule at the fusion centre (FC) has been shown to be the weighted distance from the soft decision mean under the null hypothesis. But as the optimal rule requires a-priori knowledge that is difficult to attain in practice, suboptimal fusion rules are proposed that are realizable in practice. We show how the effect of quantizing the test statistic can be mitigated by increasing the number of SN samples, i.e., bandwidth can be traded off against increased latency. The optimal power and bit allocation for the WSN is also derived. Simulation results show that SNs with good channels are allocated more bits, while SNs with poor channels are censored.

Keywords:Wireless Sensor Networks (WSNs), decision theory, Sensor fusion, signal detection, statistical testing
Subjects:H Engineering > H641 Telecommunications Engineering
H Engineering > H600 Electronic and Electrical Engineering
H Engineering > H640 Communications Engineering
Divisions:College of Science > School of Engineering
ID Code:27393
Deposited On:21 Jun 2017 08:37

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