Novel Consensus Algorithm for Wireless Sensor Networks with Noise and Interference Suppression

Abstract

Achieving consensus on common global parameters through totally decentralized algorithms is a topic that has attracted considerable attention in the last few years, in view of its potential application in sensor networks. Several algorithms, along with their convergence properties, have been studied in the literature, among which the most popular are the (weighted) average consensus based schemes. One of the most critical aspects of these algorithms is that they suffer from catastrophic noise propagation. In addition, the effect of additive interference is dramatic. In this work we propose a novel consensus algorithm which is effective in suppressing both noise and interference. In particular, the variance of the noise affecting the consensus values can be made arbitrarily low. Moreover, interferences of finite duration or periodic can be completely rejected. The proposed consensus algorithm subsumes, as a special cases, previously known algorithms. Finally, its ability in suppressing noise and interference holds regardless of the noise statistics and for arbitrary network topology.