Distributed Adaptive Filtering with Reduced Communication Load
Kozat, S. S.
European Signal Processing Conference
European Signal Processing Conference, EUSIPCO
1488 - 1492
Item Usage Stats
MetadataShow full item record
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.
Three orders of magnitude