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Unmanned aerial vehicle (UAV) networks are convinced as a significant part of5G and emerging 6G wireless networks. UAV slicing is a promising proposal ofconverging different services onto a common UAV network without deployingindividual network solution for each type of service. This paper is concernedwith UAV slicing for providing energy-efficient and fair service coverage forenhanced mobile broadband (eMBB) users (UEs). Aiming at physically configuringUAV slices, the UAV slicing problem is formulated as a time-dependentmixed-integer-non-convex programming problem with a goal of maximizing all UEs'data rates while minimizing UAVs' total transmit power. To mitigate thischallenging problem, we first decompose the original problem into twotime-dependent subproblems using a Lyapunov approach. We then derive theprocedure of tackling the non-convexity and the mixed-integer property of thesubproblems by exploring a successive convex approximate (SCA) method and analternative optimization scheme, respectively. Based on the derived results, wedevelop an algorithm with provable performance guarantees to mitigate the twosubproblems repeatedly.

Repeatedly Energy-Efficient and Fair Service Coverage: UAV Slicing  (Proactive UAV Network Slicing for URLLC and Mobile Broadband Service  Multiplexing)