Fusion of Decisions Modeled as Weak Signals in Wireless Sensor Networks

Distributed detection has newly received research interest due to the success of the emerging wireless sensor network (WSN) technology. To deal with the problem of distributed detection for the WSN having the energy constraint, the fusion of decisions modeled as weak signals is studied. By using the weak signal model and additive non-Gaussian noise channels in the canonical parallel fusion scheme, we propose an asymptotic fusion rule applicable for wide classes of noise probability density functions (pdfs). In the particular case of a known pdf, an optimal detection rule is given. Both asymptotic analysis and Monte Carlo simulation are used to examine the performance of the proposed detection fusion rule.