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: "u beas a stackelberg game for device to device communications"
  Abstract: User-behavior-aware communications will be a key feature of future generation cellular networks, so user experience is enhanced with greater benefit to users. In this paper, a user-behavior-aware Stackelberg (U-BeAS) game for device-to-device (D2D) communications overlaying cellular communications is proposed. Our proposed game provides an optimal trade-off between minimizing transmit power and maximizing packet delivery ratio (PDR), with respect to D2D user-behavior for all D2D pairs. The Stackelberg leader, base station (BS), selects its satisfaction with the social welfare of the D2D followers by considering the reaction of the followers to the price it charges. All followers (D2D pairs) select transmit power so as to guarantee a desired quality-of-experience (QoE), where each follower enacts one of three possible behaviors: (i) casual; (ii) intermediate; or (iii) serious. Analysis shows that there exists a sub-game perfect Stackelberg Equilibrium across all players. Analysis and simulation demonstrates that the BS leader rapidly converges to an optimal satisfaction while guaranteeing social welfare across D2D users, and all D2D followers then rapidly converge to a Pareto-efficient outcome with respect to transmit power and PDR.

Connected through hyperedge HE-1 (induced by source paper "spatial configuration of agile wireless networks with drone bss and user in the loop"):
  with members:
    - "on the number and 3d placement of drone base stations in wireless cellular networks"
    - "configurations and diagnosis for ultra dense heterogeneous networks from empirical measurements to technical solutions"
    - "dynamic base station repositioning to improve performance of drone small cells"
    - "placement optimization of uav mounted mobile base stations"
    - "user association and bandwidth allocation for terrestrial and aerial base stations with backhaul considerations"
    - "optimal transport theory for cell association in uav enabled cellular networks"
    - "energy efficient 3d uav bs placement versus mobile users density and circuit power"
    - "deployment and trajectory optimization for uavs a quantization theory approach"

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.NI(Networking and Internet Architecture)