Heterogeneous Service-Oriented Resource Provisioning and UAV Deployment for Aerial Edge Computing Networks

Uncrewed aerial vehicle (UAV)-assisted mobile-edge computing (MEC) has been a promising architecture to enable seamless aerial computing and communications. With evolving requirements of heterogeneous services in future wireless networks, it is challenging to realize on-demand resource management and network deployment in UAV-assisted MEC systems. This article investigates unified communication and computation resource management as well as network deployment to meet the quality of service (QoS) of enhanced mobile broadband (eMBB) and massive machine-type communication (mMTC) simultaneously. A network utility minimization problem is formulated which jointly considers UAV deployment, user association, spectrum slicing, communication, and computation resource allocation. First, a coalition game-based UAV deployment and eMBB user (eUE) association algorithm is designed, based on which a communication and computation resource allocation algorithm is devised by convex optimization. The mMTC user (mUE) association and power control is optimized via successive convex approximation. Then, a spectrum slicing and allocation algorithm is designed by the bisection search method. Finally, a joint resource allocation and network deployment scheme is proposed. Simulation results demonstrate that our proposed algorithm can effectively reduce average service delay of eUEs and increase the number of served mUEs in UAV-assisted MEC systems.