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: "performance analysis of dense scns with generalized shadowing fading and nlos los transmissions"
  Abstract: In this paper, we propose a unified framework to analyze the performance of dense small cell networks (SCNs) in terms of the coverage probability and the area spectral efficiency (ASE). A practical path loss model incorporating both non-line-of-sight (NLOS) and line-of-sight (LOS) transmissions has been considered in our analysis. Moreover, we adopt a generalized shadowing/fading model, in which log-normal shadowing and/or Rayleigh fading can be treated in a unified framework. The coverage probability and the ASE are derived, using a generalized stochastic geometry analysis based on a transformed Poisson point process (PPP). Using the analysis, we show for the first time that depending on the intensity of the BSs, the performance of the SCNs can be divided into four different regimes, i.e., the noise-limited regime, the signal NLOS-to-LOS-transition regime, the interference NLOS-to-LOS-transition regime and the dense interference-limited regime, where in each regime the performance is dominated by different factors. The analysis helps to understand as the intensity of the BSs grows continually, which dominant factor that determines the cellular network performance and therefore provide guidance on the design and management of the cellular networks as we evolve into dense SCNs.

Connected through hyperedge HE-1 (induced by source paper "performance impact of base station antenna heights in dense cellular networks"):
  with members:
    - "dynamic base station repositioning to improve performance of drone small cells"
    - "dense small cell networks from noise limited to dense interference limited"
    - "the intensity matching approach a tractable stochastic geometry approximation to system level analysis of cellular networks"
    - "please lower small cell antenna heights in 5g"
    - "performance impact of los and nlos transmissions in dense cellular networks"
    - "stochastic geometry modeling and analysis of multi tier millimeter wave cellular networks"
    - "impact of metro cell antenna pattern and downtilt in heterogeneous networks"
    - "towards 1 gbps ue in cellular systems understanding ultra dense small cell deployments"

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)