Method to modify adaptive filter weights in a decentralized wireless sensor network

Abstract

A method and a system of distributed estimation using q-diffusion least mean squares (qDiff-LMS) to modify adaptive filter weights in a decentralized wireless sensor network of N nodes is described. The method includes receiving, at each node, k, a local estimate of a previous time instance weight, w(i−1), of an adaptive filter of each neighboring node, l, where l=1, 2, . . . , M, combining the local estimates of the previous time instance weights to generate a linear combination of global diffused weights, Ø(i−1), measuring, for each node k, an output, y(i), of the adaptive filter of the node k, calculating, for each node k, a desired response, d(i); generating, for each node k, an estimation error, e(i) by subtracting the output, y(i) from the desired response, d(i), and updating the global diffused weights by adding a portion of the estimated error to the global diffused weights.