LAUSR

The paper proposes a smart method to remove network nodes that are highly prone to impulse noise and replacing them with a linear combination of existing more reliable nodes. This is done to reduce communication cost. To reduce the communication cost in a network, a common way is to remove some nodes randomly and then replace the intermediate estimation of these nodes by the corresponding node estimation. In this direction, the contribution of this paper is twofold. First, we suggest to remove the nodes smartly by omitting the unreliable nodes prone to impulsive noise. This is done by computing the disturbance induced in the adaptation step of the diffusion least mean square. Second, we replace the estimation of removing nodes by a linear combination of existing estimations of reliable nodes instead of just replacing by the estimation of the corresponding node. Also, the coefficients of linear combination are optimized based on the minimum disturbance principle. Furthermore, the minimum achievable disturbance is calculated mathematically and a necessary and sufficient condition for stability of the proposed algorithm is presented. Finally, the simulation results show the efficiency of the proposed method in comparison with some state-of-the-art algorithms.