Joint Communication and Safe 3D Path Optimization for Multi-UAV Assisted Mobile Internet of Vehicles on an Uneven Terrain

The paper studies an Internet of Vehicles system consisting of several UAVs sending downlink information to ground vehicles to move an uneven terrain. In such environments, the transmission from the UAV to the ground vehicles may be blocked by tall buildings or mountains. Our goal is to construct multi-UAV navigation laws, transmission schedules, and transmit power levels of the UAVs that maximize the total downlink throughput of the system while minimizing the total transmit power and the propulsion energy of the multi-UAV team subject to a communication interference constraint for the UAVs. An important feature of the investigation is that a safety constraint that guarantees to avoid collisions between UAVs with a required safety margin should always be satisfied. A real-time law for joint communication and multi-UAV navigation is proposed. A mathematically rigorous analysis of the developed algorithm and proof of its optimality are given. Illustrative examples and simulations demonstrate the effectiveness of the approach. The main purpose of the proposed framework is to achieve joint communication and safe 3D path optimization, which means that the objective is to jointly construct 3D paths of the UAVs, transmission schedules, and transmit power levels of the UAVs. An advantage of this approach is that it allows to simultaneously maximize the total downlink throughput of the system and minimizes the total transmit power and the propulsion energy of all the UAVs subject to safety constraints that guarantee the UAVs avoid collisions between the UAVs as well as the UAVs and the uneven terrain. Note to Practitioners —Unmanned aerial vehicles (UAVs) have been regarded as a promising platform to serve as aerial access points, especially in complex environments with tall buildings and uneven terrains where conventional ground access points might usually provide unqualified service to users. In this paper, we have investigated an Internet of Vehicles (IoV) system that involves multiple unmanned aerial vehicles (UAVs) transmitting downlink information to ground vehicles navigating through challenging terrains. Our primary objective is to develop effective multi-UAV navigation laws, transmission schedules, and transmission power allocations that optimize the total downlink throughput of the system. At the same time, we aim to minimize the overall transmit power and propulsion energy of the UAV team, while adhering to communication interference constraints. It is worth noting that ensuring safety is of utmost importance in our investigation. We have incorporated a safety constraint that guarantees the prevention of collisions between UAVs, maintaining a required safety margin at all times. To tackle these challenges, we propose a real-time law that combines dynamic programming and model predictive control techniques for joint transmission and multi-UAV trajectory planning. The developed algorithm has undergone a rigorous mathematical analysis, and we have provided proof of its optimality.