A new LMS strategy for sparse estimation in adaptive networks

Recently several algorithms have been developed to exploit the distributive nature of an ad hoc wireless sensor network to estimate a certain parameter of interest. However, no work has been done to specifically address the issue of estimation of a sparse parameter. Recently, a sparse estimation algorithm based on the LMS algorithm was proposed. This work proposes a new sparse LMS algorithm for parameter estimation in adaptive networks. Two different schemes are used for incorporating the sparse LMS algorithm into the adaptive network framework. Simulation results show that in a sparse environment the proposed algorithms perform better than the LMS algorithm.