Game-Theoretic Approaches for Wireless Communications with Unmanned Aerial Vehicles

TL;DR

This paper surveys and introduces game-theoretic methods for optimizing wireless communications with UAVs, addressing challenges like energy efficiency and coverage, and proposing mean field games for large UAV networks.

Contribution

It provides a comprehensive classification of existing game-theoretic approaches and introduces novel solutions, including the application of mean field games for large-scale UAV networks.

Findings

Game theory effectively addresses UAV communication challenges.

Mean field game approach is promising for massive UAV networks.

Game-theoretic solutions improve energy efficiency and coverage.

Abstract

Wireless communications with unmanned aerial vehicles (UAVs) offer a promising solution to provide cost-effective wireless connectivity and extend coverage. In recent years, the area of wireless communications for UAV system design and optimization has been receiving enormous attention from the research community. However, there are still existing challenges that are far from solved. To cope with those challenges, researchers have been exploring the applicability of game-theoretic approaches. This paper surveys the existing game-theoretic solutions and presents a number of novel solutions which are designed to optimize energy consumption, enhance network coverage, and improve connectivity in wireless communications with UAVs. We present main game components and the elements they represent in wireless communications with UAVs first and then give a classification of the current used game-theoretic approaches. We identify main problems in wireless communications with UAVs in which game theory has been used to find solutions. We provide a case to show the merits of applying game theory in wireless communication with UAVs. Finally, we discuss shortcomings of the traditional game-theoretic approaches and propose mean field game (MFG) as an appropriate method for solving novel technical problems in massive UAVs networks.