Performance of Wireless Communications using Unmanned Aerial Vehicles
Abstract
Use of Drone-based Communication Array: We have developed a novel framework for deploying and operating a drone-based antenna array system that delivers wireless service to a number of ground users within a minimum time. In particular, we have designed a new framework that minimizes the service time, including both the transmission time and the control time needed to control the movement and orientation of the drones. To this end, we minimize the transmission time, by optimizing the drones locations, as well as the control time that the drones need to move between these optimal locations. To minimize the transmission time, first, we determined the optimal drone spacing for which the array directivity is maximized. In this case, using perturbation theory, we solved the drone spacing optimization problem by successively solving a number of perturbed convex optimization problems. Next, given the derived drone spacing, we optimally adjusted the locations of the drones according to the position of each ground user. In order to serve different users, the drones must dynamically move between the derived optimal locations, during the control time period. To minimize the control time of quadrotor drones, we determined the optimal speeds of rotors such that the drones can update their positions and orientations within a minimum time. In this case, using bang-bang control theory, we derived a closed-form expression for the minimum control time as a function of external forces (e.g., wind and gravity), the drones weight, and the destinations of drones. Our results show that the proposed drone antenna array approach can significantly reduce the service time and improve the spectral and energy efficiency of the network. In particular, our approach yields 32% improvement in spectral efficiency compared to a case in which the same number of drones form a fixed uniform aerial antenna array.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jul 25, 2022
- Accession Number
- AD1189382
Entities
People
- Mohammad Mozaffari
- Walid Saad
Organizations
- Virginia Tech