Asymptotically optimal empirical fusion of bit estimates derived from a bank of receivers

In this paper we derive an asymptotically optimal algorithm for blindly fusing bit estimates from various distributed detectors when the performance of each detector is unknown. Results show that in practical regimes, this new fusion rule outperforms the best individual detector in the bank and outperforms the standard “majority rule” fusion detector