Link probability control for probabilistic diffusion least-mean squares over resource-constrained networks

This paper presents an efficient link probability control strategy for distributed estimation problems over probabilistic diffusion networks where the mean usage of communication resources is restricted. The proposed algorithm controls link probabilities so that the estimation error is minimized under given resource constraints. Simulation results show that the probabilistic diffusion least-mean squares (LMS) algorithm with the proposed probability control not only outperforms those with static probabilities but also reduces the amount of communications among nodes.