Digital Twin-based Aerial Mobile Edge Computing System for Next Generation 6G Networks

The rapid advancement of communication technology has driven up increasing demand for next generation sixth-generation (6G) networks to meet ultra-low latency and high connectivity specifications. In this context, unmanned aerial vehicle (UAV)-based mobile edge computing (MEC) has recently emerged as an attractive prospect by providing low latency with faster tasks offloading at the edge of the network. On the other hand, the incorporation of the digital twin (DT) concept into the aerial MEC paradigm can enable intelligence, adaptability, and efficiency, making it a potent and innovative solution for the forthcoming ultra-dense heterogeneous 6G networks. Therefore, to provide high network performance to real-time and latency-sensitive applications in 6G systems, this paper offers an innovative DT-based aerial MEC architecture that employs UAVs as aerial base stations complemented by MEC features. Moreover, an adaptive task offloading (ATO) algorithm is also developed which can provide dynamic resource allocation and intelligent decision-making ability. Additionally, simulation-based mathematical assessments further demonstrate the proposed model’s superior performance compared with conventional UAV-based MEC, highlighting its potential in shaping the future of 6G networks with enhanced scalability and higher efficiency.