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A distributed adaptive algorithm is proposed to solve a node-specificparameter estimation problem where nodes are interested in estimatingparameters of local interest and parameters of global interest to the wholenetwork. To address the different node-specific parameter estimation problems,this novel algorithm relies on a diffusion-based implementation of differentLeast Mean Squares (LMS) algorithms, each associated with the estimation of aspecific set of local or global parameters. Although all the different LMSalgorithms are coupled, the diffusion-based implementation of each LMSalgorithm is exclusively undertaken by the nodes of the network interested in aspecific set of local or global parameters. To illustrate the effectiveness ofthe proposed technique we provide simulation results in the context ofcooperative spectrum sensing in cognitive radio networks.

Distributed Diffusion-based LMS for Node-Specific Parameter Estimation over Adaptive Networks