Journal article

Distributed average consensus with quantization refinement

D Thanou, E Kokiopoulou, Y Pu, P Frossard

IEEE Transactions on Signal Processing | Published : 2013

Abstract

We consider the problem of distributed average consensus in a sensor network where sensors exchange quantized information with their neighbors. We propose a novel quantization scheme that exploits the increasing correlation between the values exchanged by the sensors throughout the iterations of the consensus algorithm. A low complexity, uniform quantizer is implemented in each sensor, and refined quantization is achieved by progressively reducing the quantization intervals during the convergence of the consensus algorithm.We propose a recurrence relation for computing the quantization parameters that depend on the network topology and the communication rate. We further show that the recurre..

View full abstract

University of Melbourne Researchers

Grants

Citation metrics