human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "throughput maximization for uav enabled wireless powered communication networks"):
  Abstract: This paper studies an unmanned aerial vehicle (UAV)-enabled wireless powered communication network (WPCN), in which a UAV is dispatched as a mobile access point (AP) to serve a set of ground users. The UAV employs the radio frequency (RF) signals based wireless power transfer (WPT) to charge the users in the downlink, and the users use the harvested RF energy to send individual information back to the UAV in the uplink. Unlike the conventional WPCN with fixed APs, the UAV-enabled WPCN can exploit the mobility of the UAV via trajectory optimization, jointly with the wireless resource allocation, to improve the system performance. In particular, we aim to maximize the uplink common throughput among all ground users over a particular finite time period, subject to the UAV's maximum speed constraint and the users' energy harvesting constraints. The decision variables include the UAV's trajectory design, as well as the UAV's downlink power allocation for WPT and the users' uplink power allocation for wireless information transfer (WIT). This problem is non-convex and thus very difficult to be solved optimally. To overcome this issue, we first consider a special case when the maximum UAV speed constraint is ignored, and obtain the optimal solution to this relaxed problem. The optimal solution shows that the UAV should hover above a finite number of ground locations over time for downlink WPT, and then hover above each user at different time for uplink WIT. Next, based on the optimal multi-location-hovering solution to the relaxed problem, we propose the successive hover-and-fly trajectory, jointly with the downlink and uplink power allocation, to efficiently solve the original problem with the maximum UAV speed constraint. Numerical results show that the proposed UAV-enabled WPCN achieves much higher uplink common throughput than the conventional WPCN with fixed-location AP.

Includes members:
  Member "capacity characterization of uav enabled two user broadcast channel":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "fundamental rate limits of uav enabled multiple access channel with trajectory optimization")
  Member "placement optimization of uav mounted mobile base stations":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "analysis of uav communications in cell free massive mimo systems")
  Member "uav enabled wireless power transfer trajectory design and energy region characterization":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "uav communications for 5g and beyond recent advances and future trends")
  Member "joint trajectory and communication design for multi uav enabled wireless networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "joint trajectory and resource allocation design for energy efficient secure uav communication systems")
  Member "energy efficient data collection in uav enabled wireless sensor network":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "joint trajectory and resource allocation design for energy efficient secure uav communication systems")
  Member "joint trajectory and communication design for uav enabled multiple access":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "uav data collection over noma backscatter networks uav altitude and trajectory optimization")
  Member "capacity of uav enabled multicast channel joint trajectory design and power allocation":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "cognitive uav communication via joint maneuver and power control")
  Member "uav enabled wireless power transfer trajectory design and energy optimization":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "joint 3d maneuver and power adaptation for secure uav communication with comp reception")

Question: Please tell me which class the source paper belongs to. The 40 classes are: cs.NA(Numerical Analysis), cs.MM(Multimedia), cs.LO(Logic in Computer Science), cs.CY(Computers and Society), cs.CR(Cryptography and Security), cs.DC(Distributed, Parallel, and Cluster Computing), cs.HC(Human-Computer Interaction), cs.CE(Computational Engineering, Finance, and Science), cs.NI(Networking and Internet Architecture), cs.CC(Computational Complexity), cs.AI(Artificial Intelligence), cs.MA(Multiagent Systems), cs.GL(General Literature), cs.NE(Neural and Evolutionary Computing), cs.SC(Symbolic Computation), cs.AR(Hardware Architecture), cs.CV(Computer Vision and Pattern Recognition), cs.GR(Graphics), cs.ET(Emerging Technologies), cs.SY(Systems and Control), cs.CG(Computational Geometry), cs.OH(Other Computer Science), cs.PL(Programming Languages), cs.SE(Software Engineering), cs.LG(Machine Learning), cs.SD(Sound), cs.SI(Social and Information Networks), cs.RO(Robotics), cs.IT(Information Theory), cs.PF(Performance), cs.CL(Computation and Language), cs.IR(Information Retrieval), cs.MS(Mathematical Software), cs.FL(Formal Languages and Automata Theory), cs.DS(Data Structures and Algorithms), cs.OS(Operating Systems), cs.GT(Computer Science and Game Theory), cs.DB(Databases), cs.DL(Digital Libraries), cs.DM(Discrete Mathematics). Directly output the class name.

gpt: cs.IT(Information Theory)