Geometry-based stochastic channel modeling method for industrial internet of things communications

Abstract

Disclosed by the present disclosure is a geometry-based stochastic channel modeling method for an IIoT channel. The method includes the following steps: S, setting a propagation scenario, propagation conditions, model parameters, an antenna configuration, and the like, S, generating large-scale parameters with a spatial consistency; S, determining a number of initial clusters, a number of specular multipath components generated in each of clusters and a number of dense multipath components generated in each of the clusters, determining a visibility of an array antenna to the clusters, generating an initial delay of the clusters, an angle of the clusters, and a power of the clusters, and generating channel coefficients between each pair of transmitter antennas and receiver antennas; S, updating the positions of the transmitters and the positions of the receivers as well as values for the large-scale parameters according to the motion trajectories of the transmitters and the motion trajectories of the receivers; S, applying a birth and death process of the clusters to initialize new clusters and update angles, delays and powers of surviving clusters, and generating the channel coefficients; and S, returning to Step S, until traversing motion trajectories of the transmitters and the motion trajectories of the receivers; calculating statistical characteristics of the channel, and verifying channel model according to actual measurement data. For the first time, the present disclosure considers 6G channel modeling requirements and dense multipath characteristics, and are verified through actual measurements, which is of great significance for the standardization of IIoT channel models.