DUAL-FAIRNESS DRIVEN 3D TRAJECTORY DESIGN AND RESOURCE ALLOCATION FOR UAV-ASSISTED ISAC SYSTEMS

Abstract

Unmanned Aerial Vehicles (UAVs), recognized for their high flexibility and rapid deployment, are increasingly utilized as key platforms for Integrated Sensing and Communication (ISAC). However, balancing on-demand service quality for users with robust sensing coverage for targets remains a critical challenge, especially in emergency scenarios where blind spots must be avoided. This paper proposes a dual-fairness framework for a UAV-assisted ISCC system. We formulate a joint optimization problem of sensing, computation, communication scheduling, and UAV 3D trajectory. To ensure service fairness among users, we adopt a logarithmic utility function to maximize the sum of the logarithm of user-received data volume. Simultaneously, to guarantee sensing fairness, we enforce a Minimum Sensing Rate Ratio (MSRR) constraint, ensuring that no target is persistently neglected. The formulated non-convex problem is solved via a proposed four-stage Alternating Optimization (AO) algorithm. Simulation results demonstrate that the proposed scheme effectively balances user service fairness with sensing robustness, achieving high-quality data delivery while strictly satisfying the sensing fairness requirements.