Frequency-Dependent Line-of-Sight Probability Modeling in Built-Up Environments

Abstract

Powered by the Internet of Things (IoT), the cellular, vehicular, and other emerging networks, such as space–air–ground integrated networks, are expected to comprehensively evolve into the new era of the Internet of Everything (IoE) in which the propagation links between the IoT devices or sensors become diversified. Thus, a general propagation channel model is required. The line-of-sight (LOS) probability plays an essential role in the channel modeling, especially for built-up environments where the blockages from buildings are unfavorable to the signal transmission. The 4-D LOS probability model with considering the 3-D environment and frequency is comprehensively investigated in this article. Using the geometry-based stochastic method, the LOS probability is derived for arbitrary sizes, heights, and orientations of buildings in finely defined urban scenarios. The major contribution is the universality, simplicity, and good extension of the proposed model with comprehensive considerations of the influence of frequency, the type of urban, and the height of transceiver. The simulation results show that the propagation with higher frequency has a higher LOS probability. Moreover, the size, height, and density of building in urban environments are closely related to the LOS probability. The good agreements of the comparisons with the ray-tracing (RT) model and standard models show the accuracy of our proposed model. These results will be useful in the modeling of various channels and the design of IoT wireless communications systems.