Energy detection for decision fusion in wireless sensor networks over Ricean-mixture fading

In this paper we focus on the energy detector for decision fusion in wireless sensor networks over multiple access channels. More specifically, we derive analytical performance in terms of global probability of false alarm and detection (including asymptotic performance for large number of sensors) when the fading is a Ricean mixture, i.e. channel coefficients are sampled from a Gaussian mixture (GM) distribution. The motivation for the GM is the ability to model real-world scenarios while keeping mathematical tractability. Analytical results are confirmed through numerical simulations.