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: "success probability and area spectral efficiency of a vanet modeled as a cox process"
  Abstract: This paper analyzes the performance of a vehicular ad hoc network (VANET) modeled as a Cox process, where the spatial layout of the roads is modeled by a Poisson line process (PLP) and the locations of nodes on each line are modeled as a 1D Poisson point process (PPP). For this setup, we characterize the success probability of a typical link and the area spectral efficiency (ASE) of the network assuming slotted ALOHA as the channel access scheme. We then concretely establish that the success probability of a typical link in a VANET modeled using a Cox process converges to that of a 1D and 2D PPP for some extreme values of the line and node densities. We also study the trends in success probability as a function of the system parameters and show that the optimum transmission probability that maximizes the ASE for this Cox process model differs significantly from those of the relatively-simpler 1D and 2D PPP models used commonly in the literature to model vehicular networks.

Connected through hyperedge HE-1 (induced by source paper "coverage and rate analysis of downlink cellular vehicle to everything c v2x communication"):
  with members:
    - "stochastic geometry modeling of cellular v2x communication over shared channels"
    - "how to dimension 5g network when users are distributed on roads modeled by poisson line process"
    - "poisson cox point processes for vehicular networks"
    - "characterizing shortest paths in road systems modeled as manhattan poisson line processes"
    - "an analytical framework for coverage in cellular networks leveraging vehicles"
    - "coverage analysis of a vehicular network modeled as cox process driven by poisson line process"
    - "modeling and design of millimeter wave networks for highway vehicular communication"
    - "mmwave vehicle to infrastructure communication analysis of urban microcellular networks"

Connected through hyperedge HE-2 (induced by source paper "stochastic geometry modeling of cellular v2x communication over shared channels"):
  with members:
    - "an analytical framework for coverage in cellular networks leveraging vehicles"
    - "coverage analysis of a vehicular network modeled as cox process driven by poisson line process"
    - "asymptotic blind spot analysis of localization networks under correlated blocking using a poisson line process"
    - "a primer on cellular network analysis using stochastic geometry"
    - "artificial noise aided secure transmission in large scale spectrum sharing networks"
    - "physical layer security in three tier wireless sensor networks a stochastic geometry approach"
    - "d2d based v2v communications with latency and reliability constraints"
    - "on stochastic geometry modeling of cellular uplink transmission with truncated channel inversion power control"

Connected through hyperedge HE-3 (induced by source paper "characterizing shortest paths in road systems modeled as manhattan poisson line processes"):
  with members:
    - "spatial networks with wireless applications"
    - "poisson cox point processes for vehicular networks"
    - "an analytical framework for coverage in cellular networks leveraging vehicles"
    - "coverage analysis of a vehicular network modeled as cox process driven by poisson line process"
    - "mmwave vehicle to infrastructure communication analysis of urban microcellular 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)