Distributed Diffusion-Based LMS for Node-Specific Adaptive Parameter Estimation

Abstract

A distributed adaptive algorithm is proposed to solve a node-specific parameter estimation problem where nodes are interested in estimating parameters of local interest, parameters of common interest to a subset of nodes and parameters of global interest to the whole network. To address the different node-specific parameter estimation problems, this novel algorithm relies on a diffusion-based implementation of different Least Mean Squares (LMS) algorithms, each associated with the estimation of a specific set of local, common or global parameters. Coupled with the estimation of the different sets of parameters, the implementation of each LMS algorithm is only undertaken by the nodes of the network interested in a specific set of local, common or global parameters. The study of convergence in the mean sense reveals that the proposed algorithm is asymptotically unbiased. Moreover, a spatial-temporal energy conservation relation is provided to evaluate the steady-state performance at each node in the mean-square sense. Finally, the theoretical results and the effectiveness of the proposed technique are validated through computer simulations in the context of cooperative spectrum sensing in Cognitive Radio networks.

13 pages, 6 figures

References in corpus (2)

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

Cited by in corpus (16)

• Distributed Clustering and Learning Over Networks
• Multitask learning over graphs: An Approach for Distributed, Streaming Machine Learning
• Online Distributed Learning Over Networks in RKH Spaces Using Random Fourier Features
• Proximal Multitask Learning over Networks with Sparsity-inducing Coregularization
• Diffusion LMS for Multitask Problems with Local Linear Equality Constraints
• Multitask diffusion adaptation over networks with common latent representations
• Adaptive Diffusion Schemes for Heterogeneous Networks
• Resilient Distributed Diffusion in Networks with Adversaries
• Adaptation and learning over networks under subspace constraints -- Part I: Stability Analysis
• Decentralized Sparse Multitask RLS over Networks
• A Multitask Diffusion Strategy with Optimized Inter-Cluster Cooperation
• Distributed Universal Adaptive Networks
• Resilient Distributed Diffusion for Multi-task Estimation
• Potential Games for Distributed Constrained Consensus
• On the Asymptotic Bias of the Diffusion-Based Distributed Pareto Optimization
• Privacy-Preserving Distributed Projection LMS for Linear Multitask Networks