A General 3-D Geometry-Based Stochastic Channel Model for B5G mmWave IIoT

The Industrial Internet of Things (IIoT) is one of the typical application scenarios in the beyond fifth generation (B5G) wireless communication systems. Due to numerous metal obstacles and machines, the industrial channel, especially at the millimeter-wave (mmWave) bands, exhibits complex characteristics that have not been considered in existing literature. This article proposes an innovative 3-D nonstationary geometry-based stochastic model (GBSM) for IIoT scenarios at mmWave bands. In the proposed model, device reflections (DRs) caused by massive metal machines are modeled based on geometrical optics. Furthermore, the generalized extreme value (GEV) distribution and generalized Pareto (GP) distribution are used to parameterize the number of clusters and rays within a cluster, respectively. Further, the Doppler shift is modeled and analyzed using the Gaussian distribution. Some channel statistical characteristics are captured by the proposed model, such as the power delay profile, root-mean-square delay spread, root-mean-square angle spread, intercluster delay, and space-time-frequency correlation function. Then, these channel statistical characteristics are well fitted to the ray-tracing simulations and the channel measurements. The excellent fitting results demonstrate the high accuracy of the proposed model, which is crucial for future IIoT communication system design. What is more, this article shows the antenna height and propagation scenarios can significantly affect the DR ratio, which should adapt to various IIoT communication scenarios.