A Hybrid Framework of Reinforcement Learning and Convex Optimization for UAV-Based Autonomous Metaverse Data Collection

Unmanned aerial vehicles (UAVs) are promising for providing communication services due to their advantages in cost and mobility, especially in the context of the emerging Metaverse and Internet of Things (IoT). This article considers a UAV-assisted Metaverse network, in which UAVs extend the coverage of the base station (BS) to collect the Metaverse data generated at roadside units (RSUs). Specifically, to improve the data collection efficiency, resource allocation and trajectory control are integrated into the system model. The time-dependent nature of the optimization problem makes it non-trivial to be solved by traditional convex optimization methods. Based on the proposed UAV-assisted Metaverse network system model, we design a hybrid framework with reinforcement learning and convex optimization to cooperatively solve the time-sequential optimization problem. Simulation results show that the proposed framework is able to reduce the mission completion time with a given transmission power resource.

Introduction

Metaverse is an emerging concept that aims to generate the digital duality of the physical world and provide users with immersive experience through augmented reality (AR), virtual reality (VR), and other novel techniques [1]. To ensure the quality of service (QoS), 5G or future 6G communication technologies are needed to support the required transmission rate of AR/VR service. However, the improvement of transmission rate is at the cost of the coverage area of one single base station (BS) due to severe attenuation of signals, which makes it more expensive to provide wireless communication coverage. On the other hand, the maintenance and update of the virtual world in Metaverse is based on massive data collected by individual devices, roadside units (RSUs), and other Internet of Things (IoT) devices. Thus, it is prominent to extend the coverage of Metaverse data collection and synchronization to provide more users with seamless service.