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: "a unified fading model using infinitely divisible distributions"
  Abstract: This paper proposes to unify fading distributions by modeling the magnitude-squared of the instantaneous channel gain as an infinitely divisible random variable. A random variable is said to be infinitely divisible, if it can be written as a sum of $n \geq 1$ independent and identically distributed random variables, for each $n$. Infinitely divisible random variables have many interesting mathematical properties, which can be applied in the performance analysis of wireless systems. It is shown that the proposed unification subsumes several unifications of fading distributions previously proposed in the wireless communications literature. In fact, almost every distribution used to model multipath, shadowing and composite multipath/shadowing is shown to be included in the class of infinitely divisible random variables.

Connected through hyperedge HE-1 (induced by source paper "performance limits of network densification"):
  with members:
    - "coverage and capacity scaling laws in downlink ultra dense cellular networks"
    - "how dense is ultra dense for wireless networks from far to near field communications"
    - "impact of los nlos propagation and path loss in ultra dense cellular networks"
    - "performance impact of los and nlos transmissions in dense cellular networks"
    - "towards 1 gbps ue in cellular systems understanding ultra dense small cell deployments"
    - "spectral efficiency scaling laws in dense random wireless networks with multiple receive antennas"
    - "downlink cellular network analysis with multi slope path loss models"
    - "modeling and analysis of k tier downlink heterogeneous cellular networks"

Connected through hyperedge HE-2 (induced by source paper "coverage and capacity scaling laws in downlink ultra dense cellular networks"):
  with members:
    - "towards 1 gbps ue in cellular systems understanding ultra dense small cell deployments"
    - "28 ghz and 73 ghz millimeter wave indoor propagation measurements and path loss models"
    - "downlink cellular network analysis with multi slope path loss models"
    - "modeling and analysis of k tier downlink heterogeneous cellular networks"
    - "a tractable approach to coverage and rate in cellular networks"
    - "best signal quality in cellular networks asymptotic properties and applications to mobility management in small cell networks"

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)