Uncrewed Vehicles in 6G Networks: A Unifying Treatment of Problems, Formulations, and Tools

TL;DR

This paper addresses the challenge of integrating uncrewed vehicles into 6G networks by proposing a unifying framework that links UV mobility, channel modeling, and network optimization. It surveys core UV-6G interactions, categorizes problem formulations for UVs as providers and consumers, and presents analytical and learning-based optimization tools including DRL, MILPs/MIPs, and dynamic programming. The contributions include a structured taxonomy of UV-driven use cases, a high-level optimization formulation, and representative problem templates that span resource allocation, ISAC, relaying, and data collection under stochastic channels. The work highlights practical significance for enabling dynamic UV-enabled coverage, sensing, edge computing, and secure communications in 6G, while identifying open challenges in high-fidelity modeling, computation, and security.

Abstract

Uncrewed Vehicles (UVs) functioning as autonomous agents are anticipated to play a crucial role in the 6th Generation of wireless networks. Their seamless integration, cost-effectiveness, and the additional controllability through motion planning make them an attractive deployment option for a wide range of applications, both as assets in the network (e.g., mobile base stations) and as consumers of network services (e.g., autonomous delivery systems). However, despite their potential, the convergence of UVs and wireless systems brings forth numerous challenges that require attention from both academia and industry. This paper then aims to offer a comprehensive overview encompassing the transformative possibilities as well as the significant challenges associated with UV-assisted next-generation wireless communications. Considering the diverse landscape of possible application scenarios, problem formulations, and mathematical tools related to UV-assisted wireless systems, the underlying core theme of this paper is the unification of the problem space, providing a structured framework to understand the use cases, problem formulations, and necessary mathematical tools. Overall, the paper sets forth a clear understanding of how uncrewed vehicles can be integrated in the 6G ecosystem, paving the way towards harnessing the full potential at this intersection.

Figures (11)

• Figure 1: Key performance indicators (KPI) for 5G IMT-2020 and 6G IMT-2030.
• Figure 2: A high-level view of the various roles UVs play in the 6G ecosystem.
• Figure 3: Sample envisioned applications of UVs as providers in next-generation communication systems. (Top left) As part of a Space-Air-Ground Integrated Network (SAGIN), a HAPS provides connectivity to isolated and underserved areas. (Top right) A UV uses ISAC to simultaneously extend connectivity to and further sense end users. (Bottom left) UVs aid a base station by acting as relays. Their elevated position allows them to serve users in dead zones, and by working together, they can extend the area covered by the terrestrial base station (TBS). (Bottom right) A team of UVs provides dynamic network provisioning for a crowd during a large event.
• Figure 4: Sample common tasks for UV operation in 6G networks. (Top left) A UV navigates to a destination while maintaining connectivity. (Top right) A UV collects data from a dynamic WSN. (Bottom left) A UV must jointly plan its trajectory and transmission power/communication rate while offloading data to a remote station. (Bottom right) A UV, initially disconnected from the network, seeks to reconnect as quickly as possible.
• Figure 5: A UV acting as a base station must support concurrent users while mitigating inter-cell interference.