A Statistical Sensing Channel Modeling Framework

Integrated sensing and communication (ISAC) is considered as an essential step in the Sixth Generation (6G) communication systems development. However, there are hardly available complete channel modeling frameworks for sensing. Conventional channel models for communication are often difficult to apply to perceptual matters. In this paper, a target-level statistical modeling framework for sensing channels is proposed with an exemplary model, which contains a discrimination of multipaths based on the bouncing number. The steps, methodologies and data flows contained therein are discussed to lay the foundation for further enrichment and expansion.