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: "exploiting noma for uav communications in large scale cellular networks"
  Abstract: This paper advocates a pair of strategies in non-orthogonal multiple access (NOMA) in unmanned aerial vehicles (UAVs) communications, where multiple UAVs play as new aerial communications platforms for serving terrestrial NOMA users. A new multiple UAVs framework with invoking stochastic geometry technique is proposed, in which a pair of practical strategies are considered: 1) the UAV-centric strategy for offloading actions and 2) the user-centric strategy for providing emergency communications. In order to provide practical insights for the proposed NOMA assisted UAV framework, an imperfect successive interference cancelation (ipSIC) scenario is taken into account. For both UAV-centric strategy and user-centric strategy, we derive new exact expressions for the coverage probability. We also derive new analytical results for orthogonal multiple access (OMA) for providing a benchmark scheme. The derived analytical results in both user-centric strategy and UAV-centric strategy explicitly indicate that the ipSIC coefficient is a dominant component in terms of coverage probability. Numerical results are provided to confirm that i) for both user-centric strategy and UAV-centric strategy, NOMA assisted UAV cellular networks is capable of outperforming OMA by setting power allocation factors and targeted rate properly; and ii) the coverage probability of NOMA assisted UAV cellular framework is affected to a large extent by ipSIC coefficient, target rates and power allocations factors of paired NOMA users.

Connected through hyperedge HE-1 (induced by source paper "secrecy transmission in large scale uav enabled wireless networks"):
  with members:
    - "a survey of optimization approaches for wireless physical layer security"
    - "exploiting noma oma for multi uav communications in large scale networks"
    - "capacity characterization of uav enabled two user broadcast channel"
    - "securing uav communications via joint trajectory and power control"
    - "cellular enabled uav communication a connectivity constrained trajectory optimization perspective"
    - "ultra reliable uav communication using altitude and cooperation diversity"
    - "physical layer security in cache enabled cooperative small cell networks against randomly distributed eavesdroppers"
    - "multiple antenna aided noma in uav networks a stochastic geometry approach"

Connected through hyperedge HE-2 (induced by source paper "joint access and backhaul resource management in satellite drone networks a competitive market approach"):
  with members:
    - "a vision of 6g wireless systems applications trends technologies and open research problems"
    - "beyond 5g with uavs foundations of a 3d wireless cellular network"
    - "liquid state machine learning for resource and cache management in lte u unmanned aerial vehicle uav networks"
    - "backhaul aware placement of a uav bs with bandwidth allocation for user centric operation and profit maximization"
    - "wireless communication using unmanned aerial vehicles uavs optimal transport theory for hover time optimization"
    - "beam tracking for uav mounted satcom on the move with massive antenna array"
    - "user association and bandwidth allocation for terrestrial and aerial base stations with backhaul considerations"
    - "mobile unmanned aerial vehicles uavs for energy efficient internet of things communications"

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)