# Power Efficient Trajectory Optimization for the Cellular-Connected Aerial Vehicles

## TL;DR

This paper proposes an iterative algorithm for optimizing the trajectory of cellular-connected aerial vehicles to minimize propulsion power while maintaining reliable communication links, addressing a complex non-convex problem.

## Contribution

It introduces a novel trajectory optimization method using successive convex approximation for energy-efficient aerial vehicle operations with connectivity constraints.

## Key findings

- The proposed algorithm effectively reduces propulsion power consumption.
- The reformulation enables efficient solutions to a complex non-convex problem.
- The method ensures reliable communication links during flight.

## Abstract

Aerial vehicles have recently attracted significant attention in a variety of commercial and civilian applications due to their high mobility, flexible deployment and cost-effectiveness. To leverage these promising features, the aerial users have to satisfy two critical requirements: First, they have to maintain a reliable communication link to the ground base stations (GBSs) throughout their flights, to support command and control data flows. Second, the aerial vehicles have to minimize their propulsion power consumption to remain functional until the end of their mission. In this paper, we study the trajectory optimization problem for an aerial user flying over an area including a set of GBSs. The objective of this problem is to find the trajectory of the aerial user so that the total propulsion-related power consumption of the aerial user is minimized while a cellular-connectivity constraint is satisfied. This problem is a non-convex mixed integer non-linear problem and hence, it is challenging to find the solution. To deal with, first, the problem is relaxed and reformulated to a more mathematically tractable form. Then, using successive convex approximation (SCA) technique, an iterative algorithm is proposed to convert the problem into a sequence of convex problems which can be solved efficiently.