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: "analysis of data harvesting by unmanned aerial vehicles"
  Abstract: This paper explores an emerging wireless architecture based on Unmanned Aerial Vehicles (UAVs), i.e., drones. We consider a network where UAVs at fixed altitude harvest data from Internet-of-Things (IoT) devices on the ground. In such a system, the UAVs' motion activates IoT uplink transmissions and so the motion triggers the interference field and determines the network performance. To analyze the performance, we propose a stochastic geometry model. The coverage area of each UAV, referred to as the activation window, is modeled for simplicity as a rectangle where at most one IoT device is scheduled to transmit at a time. In this setting, we analyze the signal-to-interference and data rate from two typical perspectives, namely from a typical UAV's and from a typical IoT device's points of view. Our stochastic geometry model enables us to explore the size of the activation window which maximizes the UAV networks' harvesting capacity. Finally, we present a network extension of the proposed model and derive the network performance.

Connected through hyperedge HE-1 (induced by source paper "multi antenna uav data harvesting joint trajectory and communication optimization"):
  with members:
    - "3d trajectory optimization in rician fading for uav enabled data harvesting"
    - "comp in the sky uav placement and movement optimization for multi user communications"
    - "energy minimization for wireless communication with rotary wing uav"
    - "energy efficient data collection in uav enabled wireless sensor network"

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)