The meta distribution of the SIR in joint communication and sensing networks

In this paper, we introduce a novel mathematical framework for assessing the performance of joint communication and sensing (JCAS) in wireless networks, employing stochastic geometry as an analytical tool. We focus on deriving the meta distribution of the signal-to-interference ratio (SIR) for JCAS networks. This approach enables a fine-grained quantification of individual user or radar performance intrinsic to these

networks. Our work involves the modeling of JCAS networks and the derivation of exact mathematical expressions for the JCAS SIR meta distribution. Recognizing the computational complexity of these expressions, we also present practical, tight

approximations. Through simulations, we validate both our exact and approximated theoretical analysis and illustrate how the JCAS SIR meta distribution varies with the network deployment density.