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A noise-constrained algorithm for estimation over distributed networks
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DOI：10.1002/acs.2358.png)
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Abstract
En 中文
Much research has been devoted recently to the development of algorithms to utilize the distributed structure of an ad hoc wireless sensor network for the estimation of a certain parameter of interest. A successful solution is the algorithm called the diffusion least mean squares algorithm. The algorithm estimates the parameter of interest by employing cooperation between neighboring sensor nodes within the network. The present work derives a new algorithm by using the noise constraint that is based on and improves the diffusion least mean squares algorithm. In this work, first the derivation of the noise constraint-based algorithm is given. Second, detailed convergence and steady-state analyses are carried out, including analyses for the case where there is mismatch in the noise variance estimate. Finally, extensive simulations are carried out to test the robustness of the proposed algorithm under different scenarios, especially the mismatch scenario. Moreover, the simulation results are found to corroborate the theoretical results very well. Copyright (c) 2012 John Wiley & Sons, Ltd.
Keywords:
noise-constrained LMS algorithm
diffusion LMS algorithm
distributed networks
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