154159
20190316234929.0
CONF
Polynomial Filter Design for Quantized Consensus
2010
2010
Conference Papers
We consider the problem of distributed average consensus where sensors exchange quantized data with their neighbors. We deploy a polynomial filtering approach in the network nodes in order to accelerate the convergence of the consensus problem. The quantization of the values computed by the sensors however imposes a careful design of the polynomial filter. We first study the impact of the quantization noise in the performance of accelerated consensus based on polynomial filtering. It occurs that the performance is clearly penalized by the quantization noise, whose impact directly depends on the filter coefficients. We then formulate a convex optimization problem for determining the coefficients of a polynomial filter, which is able to control the quantization noise while accelerating the convergence rate. The simulation results show that the proposed solution is robust to quantization noise while assuring a high convergence speed to the average value in the network.
Distributed averaging
Distributed consensus
Polynomial filtering
Uniform quantization
LTS4
Thanou, Dorina
185309
244101
Park, Hyung Gon
Kokiopoulou, Effrosyni
170201
240462
Frossard, Pascal
101475
241061
European Signal Processing Conference (EUSIPCO)
Aalborg, Denmark
August 23-27, 2010
Proceedings of the 18th European Signal Processing Conference
n/a
206334
n/a
http://infoscience.epfl.ch/record/154159/files/1569291261.pdf
LTS4
252393
U10851
oai:infoscience.tind.io:154159
STI
conf
GLOBAL_SET
185309
101475
EPFL-CONF-154159
EPFL
PUBLISHED
REVIEWED
CONF