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: "statistical modeling of fso fronthaul channel for drone based networks"
  Abstract: We consider a drone-based communication network, where several drones hover above an area and serve as mobile remote radio heads for a large number of mobile users. We assume that the drones employ free space optical (FSO) links for fronthauling of the users' data to a central unit. The main focus of this paper is to quantify the geometric loss of the FSO channel arising from random fluctuation of the position and orientation of the drones. In particular, we derive upper and lower bounds, corresponding approximate expressions, and a closed-form statistical model for the geometric loss. Simulation results validate our derivations and quantify the FSO channel quality as a function of the drone's instability, i.e., the variation of its position and orientation.

Connected through hyperedge HE-1 (induced by source paper "intelligent reflecting surfaces for free space optical communications"):
  with members:
    - "enabling secure wireless communications via intelligent reflecting surfaces"
    - "reflect and transmit array antennas for scalable and energy efficient mmwave massive mimo"
    - "intelligent reflecting surface enhanced wireless network via joint active and passive beamforming"
    - "intelligent reflecting surface enhanced wireless network joint active and passive beamforming design"
    - "optimization of free space optical wireless network for cellular backhauling"

Connected through hyperedge HE-2 (induced by source paper "optimal 3d trajectory design and resource allocation for solar powered uav communication systems"):
  with members:
    - "fundamental tradeoffs in communication and trajectory design for uav enabled wireless network"
    - "capacity characterization of uav enabled two user broadcast channel"
    - "resource allocation for solar powered uav communication systems"
    - "energy minimization for wireless communication with rotary wing uav"
    - "common throughput maximization in uav enabled ofdma systems with delay consideration"
    - "optimal resource allocation for power efficient mc noma with imperfect channel state information"
    - "joint trajectory and communication design for multi uav enabled wireless networks"
    - "securing uav communications via trajectory optimization"

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)