Consensus-based distributed detection algorithm in wireless ad hoc networks

This paper presents the consensus-based distributed detection (CBDD) algorithm for wireless ad hoc networks, where no fusion center is involved in collecting local information and all nodes reach global decision consensus based on local information exchange. The convergence properties and probability of error of the CBDD algorithm are investigated assuming independent and identically distributed (i.i.d.) Gaussian observations with shifted mean under both an ideal and practical multiaccess (MAC) channel. Specifically, with appropriate algorithm design, there exists an optimal number of iterations that yields the minimum probability of error. Finally, simulation results are provided to verify these analytical results.