Optimization of Time–Frequency Resource Management Based on Probabilistic Graphical Models in Railway Internet-of-Things Networking

As the high-speed railway (HSR) industry Internet-of-Things chain matures, HSR wireless communication technology has become an increasingly important research field. The efficient management of time–frequency resources for Internet-of-Things networking is the core issue of HSR wireless communication optimization. The lack of time–frequency resources in LTE-R is still severe. In this article, a new LTE-R time–frequency resource allocation optimization method based on the probabilistic graphical theory is proposed. Considering the regularity that high-speed trains always pass by the same geographical location in similar time periods, we can do some research on opportunistic spectrum accessibility in the existing LTE time–frequency resource algorithm. The probabilistic graphical theory is suitable for finding the appropriate communication access opportunity in an HSR environment. The simulation results show that our method can effectively improve the performance of various traditional LTE time–frequency resource allocation algorithms.