human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "optimal 1d trajectory design for uav enabled multiuser wireless power transfer"
  Abstract: In this paper, we study an unmanned aerial vehicle (UAV)-enabled wireless power transfer (WPT) network, where a UAV flies at a constant altitude in the sky to provide wireless energy supply for a set of ground nodes with a linear topology. Our objective is to maximize the minimum received energy among all ground nodes by optimizing the UAV's one-dimensional (1D) trajectory, subject to the maximum UAV flying speed constraint. Different from previous works that only provided heuristic and locally optimal solutions, this paper is the first work to present the globally optimal 1D UAV trajectory solution to the considered min-energy maximization problem. Towards this end, we first show that for any given speed-constrained UAV trajectory, we can always construct a maximum-speed trajectory and a speed-free trajectory, such that their combination can achieve the same received energy at all these ground nodes. Next, we transform the original UAV-speed-constrained trajectory optimization problem into an equivalent UAV-speed-free problem, which is then optimally solved via the Lagrange dual method. The obtained optimal 1D UAV trajectory solution follows the so-called successive hover-and-fly (SHF) structure, i.e., the UAV successively hovers at a finite number of hovering points each for an optimized hovering duration, and flies among these hovering points at the maximum speed. Numerical results show that our proposed optimal solution significantly outperforms the benchmark schemes in prior works under different scenarios.

Connected through hyperedge HE-1 (induced by source paper "common throughput maximization for uav enabled interference channel with wireless powered communications"):
  with members:
    - "uav communications for 5g and beyond recent advances and future trends"
    - "fundamentals of wireless information and power transfer from rf energy harvester models to signal and system designs"
    - "capacity characterization of uav enabled two user broadcast channel"
    - "cellular enabled uav communication a connectivity constrained trajectory optimization perspective"
    - "minimum throughput maximization in uav aided wireless powered communication networks"
    - "a tutorial on uavs for wireless networks applications challenges and open problems"
    - "uav enabled wireless power transfer with directional antenna a two user case"
    - "throughput maximization for uav enabled wireless powered communication networks"

Connected through hyperedge HE-2 (induced by source paper "interference avoidance position planning in dual hop and multi hop uav relay networks"):
  with members:
    - "dynamic mobility aware interference avoidance for aerial base stations in cognitive radio networks"
    - "local map assisted positioning for flying wireless relays"
    - "cellular enabled uav communication a connectivity constrained trajectory optimization perspective"
    - "joint trajectory and communication design for multi uav enabled wireless networks"
    - "network formation in the sky unmanned aerial vehicles for multi hop wireless backhauling"
    - "energy efficient uav communication with trajectory optimization"
    - "wireless communications with unmanned aerial vehicles opportunities and challenges"
    - "mobile internet of things can uavs provide an energy efficient mobile architecture"

Question: Please tell me which class the center node 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)