Joint optimization of transmission and propulsion in aerial communication networks

TL;DR

This paper develops a joint optimization framework for minimizing both transmission and propulsion energy in autonomous aerial communication networks, demonstrating potential energy savings and throughput improvements through combined control strategies.

Contribution

It introduces a novel nonlinear optimal control problem that models both communication and locomotion energies, transforming it into a convex form for efficient solution, applicable to multi-node UAV networks.

Findings

Transmission and propulsion energies are of similar magnitude, enabling potential energy savings.

Speed and power control strategies can significantly enhance network throughput.

The framework extends to multi-node UAV networks where previous methods are insufficient.

Abstract

Communication energy in a wireless network of mobile autonomous agents should be considered as the sum of transmission energy and propulsion energy used to facilitate the transfer of information. Accordingly, communication-theoretic and Newtonian dynamic models are developed to model the communication and locomotion expenditures of each node. These are subsequently used to formulate a novel nonlinear optimal control problem (OCP) over a network of autonomous nodes. It is then shown that, under certain conditions, the OCP can be transformed into an equivalent convex form. Numerical results for a single link between a node and access point allow for comparison with known solutions before the framework is applied to a multiple-node UAV network, for which previous results are not readily extended. Simulations show that transmission energy can be of the same order of magnitude as propulsion energy allowing for possible savings, whilst also exemplifying how speed adaptations together with power control may increase the network throughput.