Tight Performance Bounds for Distributed Detection
Gernot Fabeck, Rudolf Mathar · 2007
Evaluating the performance measures of distributed detection in sensor networks is important for design procedures aiming at optimal configurations. Direct computation of the global error probabilities is a difficult problem and feasible only in some special cases. In this paper, we present an approach that provides closed-form upper bounds on the detection error probabilities in the parallel fusion network which are both computationally simple and numerically tight. The bounds are derived by combining a probability inequality formulated by Hoeffding with a multiplicative form factor which is due to Talagrand. We demonstrate that the bounds apply to sensor networks of varying size, an arbitrary number of local quantization levels, and non-identical sensors.