A Hilbert-Huang Transform-Based Traffic Estimation Algorithm to Power Line Communications

Network traffic is significantly difficult be correctly estimated and predicted in power line communications because network traffic has obvious dynamic features. How to accurately estimate and predict network traffic in power communication networks is very significant for power scheduling. This paper studies the network traffic estimation problem in power line telecommunications and proposes a new estimation method to accurately forecast power communication network traffic. Firstly, we use the Hibert-Huang transform theory to capture network traffic features in power line communications. Secondly, we construct the Hibert-Huang transform estimation model about network traffic in power line communications to forecast dynamic network traffic. Thirdly, we propose a new traffic estimation algorithm to estimate network traffic. Simulation results show that our approach is feasible.