Network-Layer Delay Provisioning for Integrated Sensing and Communication UAV Networks Under Transient Antenna Misalignment

Unmanned aerial vehicle (UAV) is expected to bring transformative improvements to the integrated sensing and communication (ISAC) systems, due to its high flexibility, high autonomy, large coverage and strong adaptability to various terrains. Sensory data is gathered by sensing UAVs (SUs) from the coverage area and then relayed to the corresponding fusion center UAVs (FCUs). Afterwards, terrestrial base stations receive the sensory data from FCUs in such air-ground networks. However, due to complex task execution environment and transmission environment, it is challenging to capture the network-layer performance of the sensory data transmission and evaluate the trade-off relationship between sensing and communication. In this work, we model and analyze the network-layer delay violation for an ISAC UAV network to address this challenge. Specifically, the UAV formation is distributed according to a Poisson cluster process (PCP). Then, the successful sensing probability is derived, with which the sensory data traffic can be captured. Under the sensory data flow, the delay violation probability is calculated for the two-stage sensory data transmission queue by exploiting stochastic network calculus (SNC). Furthermore, a delay minimization problem is proposed to reveal the trade-off relationship between sensing and communication under the power allocation strategy. Based on the long-term network-layer queue backlog evaluated, we are devoted to analyze the delay violation probability under an emergency that results in the antenna misalignment for one typical sensing UAV during a certain period. The steady-state and transient analysis for the ISAC UAV network not only illustrate the trade-off relationship between sensing and communication for the network, but also provide insights for on-demand power allocation, network deployment, control module provisioning and sensory data flow control under certain performance requirements.