Distributed adaptive filtering with reduced communication load
Date
2016Source Title
Proceedings of the 24th European Signal Processing Conference, EUSIPCO 2016
Print ISSN
2219-5491
Publisher
IEEE
Pages
1488 - 1492
Language
English
Type
Conference PaperItem Usage Stats
132
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98
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Abstract
We propose novel algorithms for distributed processing in applications constrained by available communication resources, using diffusion strategies that achieve up to three orders-of-magnitude reduction in communication load on the network, while delivering equal performance with respect to the state of the art. After computation of local estimates, the information is diffused among processing elements (or nodes) non-uniformly in time by conditioning the information transfer on level-crossings of the diffused parameter, resulting in a greatly reduced communication requirement. We provide the mean stability analysis of our algorithms, and illustrate the gain in communication efficiency compared to other reducedcommunication distributed estimation schemes.
Keywords
Signal processingCommunication efficiency
Communication resources
Diffusion strategies
Distributed estimation
Distributed processing
Information transfers
Processing elements
Three orders of magnitude
Adaptive filters