The problem of decision fusion in distributed sensors system is considered. A parallel sensor configuration is considered in which sensors monitor a common geographical volume and relay their decisions to a fusion center. The fusion center upon reception of the decision is responsible for fusing them into the final decision. Under conditional independence assumption, it is shown that the optimal test that maximizes the probability of detection for a fixed probability of false alarm consists of a Neyman-Pearson Test at the fusion and Likelihood-Ratio Tests st the sensors. Numerical evaluation of the optimal operating points is computationally intensive. Two computationally efficient suboptimal algorithms have been developed. Numerical results from extensive simulation in Rayleigh and Gaussian channels are presented.