Channel Modeling Framework for Bistatic ISAC Under 3GPP Standard

Integrated sensing and communications (ISAC) is considered a promising technology in the B5G/6G networks. The channel model is essential for an ISAC system to evaluate the communication and sensing performance. Most existing channel modeling studies focus on the monostatic ISAC channel. In this paper, the channel modeling framework for bistatic ISAC is considered. The proposed channel modeling scheme extends the current 3GPP channel modeling framework and ensures the compatibility with the communication channel model. To support the bistatic sensing function, several key features for sensing are added. First, more clusters with weaker power are generated and retained to characterize the potential sensing targets. Second, the target model can be either deterministic or statistical, based on different sensing scenarios. Furthermore, for the statistical case, rays are generated considering spatial coherence for different reflection models. The effectiveness of the proposed bistatic ISAC channel model is validated by both Ray-tracing simulations and experiment studies. The compatibility with the 3GPP communication channel model is also demonstrated.