A Spatially Consistent Cluster-Based GBSM for Integrated Sensing and Communication Scenarios

Integrated sensing and communication (ISAC) merges the functions of environmental sensing and wireless communication into a unified system, enhancing network efficiency and performance through shared hardware and spectrum resources. To better characterize ISAC channels accurately, this paper proposes a novel cluster-based geometry-based stochastic model (GBSM) by considering the exclusive and shared clusters of communication and sensing channels. Specially, the spatial consistency of the proposed model, which is introduced through cluster evolution, is analized for better description of the consistent temporal and spatial variation of clusters. Furthermore, the conducted channel measurements show the existence of exclusive and shared clusters as well as the position estimation of environmental scatterers. Channel simulations are conducted to show the spatial consistency of the proposed model. The accuracy of the model regarding of spatial consistency is also validated by analyzing the temporal autocorrelation function (TACF) and spatial cross-correlation function (SCCF).