Stochastic Network Calculus Analysis of Spatial-Temporal Integrated Sensing and Communication Networks

Integrated sensing and communication (ISAC) is regarded as one of the key technologies for future systems due to its high spectrum efficiency and low hardware cost. However, high integration of sensing and communication also brings abundant challenges, e.g., waveform design, signal processing and fundamental performance limits, etc. In this work, we focus on the spatial-temporal delay analysis of sensory data transmission in ISAC networks. Specifically, the spatial distribution of sensing infrastructures (SIs) and fusion centers (FCs) are modeled by Matern cluster process. The Laplace transform of the interference experienced by SIs and FCs is quantificated and the service capability of sensory data transmission is obtained. With the sensory data flow characterized by successful sensing probability, the upper bound of network-layer queuing delay is analyzed via stochastic network calculus. Furthermore, we propose an optimal power allocation strategy to minimize the transmission delay, which balances sensing quality and transmission latency.