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: "an extension of the kappa mu shadowed fading model statistical characterization and applications"
  Abstract: We here introduce an extension and natural generalization of both the \kappa-\mu$\,$shadowed and the classical Beckmann fading models: the Fluctuating Beckmann (FB) fading model. This new model considers the clustering of multipath waves on which the line-of-sight (LoS) components randomly fluctuate, together with the effect of in-phase/quadrature power imbalance in the LoS and non-LoS components. Thus, it unifies a variety of important fading distributions as the one-sided Gaussian, Rayleigh, Nakagami-m, Rician, \kappa-\mu, \eta-\mu, \eta-\kappa, Beckmann, Rician shadowed and the \kappa-\mu$\,$shadowed distribution. The chief probability functions of the FB fading model, namely probability density function, cumulative distribution function and moment generating function are derived. The second-order statistics such as the level crossing rate and the average fade duration are also analyzed. These results can be used to derive some performance metrics of interest of wireless communication systems operating over FB fading channels.

Connected through hyperedge HE-1 (induced by source paper "composite fading models based on inverse gamma shadowing theory and validation"):
  with members:
    - "on the utility of the inverse gamma distribution in modeling composite fading channels"
    - "the kappa mu shadowed fading model with integer fading parameters"
    - "the fluctuating two ray fading model statistical characterization and performance analysis"
    - "mgf approach to the analysis of generalized two ray fading models"

Connected through hyperedge HE-2 (induced by source paper "performance analysis of physical layer security over fluctuating beckmann fading channels"):
  with members:
    - "on physical layer security over fox s h function wiretap fading channels"
    - "effective rate analysis over fluctuating beckmann fading channels"
    - "secrecy analysis of physical layer over kappa mu shadowed fading scenarios"
    - "secrecy outage analysis over correlated composite nakagami m gamma fading channels"
    - "secrecy capacity analysis over kappa mu fading channels theory and applications"

Connected through hyperedge HE-3 (induced by source paper "on the utility of the inverse gamma distribution in modeling composite fading channels"):
  with members:
    - "the kappa mu shadowed fading model with integer fading parameters"

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)