Measurement-Based Mixed-Bouncing Wideband Space-Time Stochastic Sensing Channel Modeling

Integrated Sensing and Communications (ISAC) has been identified as a key technology in the Sixth-Generation (6G) as an enabler for environment-aware communications. Although many communications-centric channel models have been developed for dynamic scenarios, they can hardly be used for sensing applications since they rely on propagation characteristics not directly related with the geometry and trajectories of the objects in the environment. On the other hand, the available sensing models are mostly deterministic, and hence not providing a stochastic description of the sensing characteristics. In this paper, we propose a sensing channel model based on geometric and kinematic parameters, such as the size, shape, position and velocity of the objects. By distinguishing between single- and multi-bounce components, the proposed channel model is able to accurately characterize propagation environments even in dense-scattered scenarios. Moreover, a novel definition is provided for the birth and death processes (BDPs), able to accurately capture the space-time correlation properties of the channels. An example of the model parametrization is provided based on actual measured data. With the channel realization approach, we exhibit the consistence between simulated and measured data and validate the efficacy of the proposed model. The work in this paper is of great significance to construct the bidirectional bridge between channel and the environment, a key point of interest for the future 6G systems.