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: "mmwave vehicle to infrastructure communication analysis of urban microcellular networks"
  Abstract: Vehicle-to-infrastructure (V2I) communication may provide high data rates to vehicles via millimeter-wave (mmWave) microcellular networks. This paper uses stochastic geometry to analyze the coverage of urban mmWave microcellular networks. Prior work used a pathloss model with a line-of-sight probability function based on randomly oriented buildings, to determine whether a link was line-of-sight or non-line-of-sight. In this paper, we use a pathloss model inspired by measurements, which uses a Manhattan distance pathloss model and accounts for differences in pathloss exponents and losses when turning corners. In our model, streets are randomly located as a Manhattan Poisson line process (MPLP) and the base stations (BSs) are distributed according to a Poisson point process. Our model is well suited for urban microcellular networks where the BSs are deployed at street level. Based on this new approach, we derive the coverage probability under certain BS association rules to obtain closed-form solutions without much complexity. In addition, we draw two main conclusions from our work. First, non-line-of-sight BSs are not a major benefit for association or source of interference most of the time. Second, there is an ultra-dense regime where deploying active BSs does not enhance coverage.

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"
    - "success probability and area spectral efficiency of a vanet modeled as a cox process"
    - "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"

Connected through hyperedge HE-2 (induced by source paper "radio resource dimensioning with cox process based user location distribution"):
  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"
    - "analytical tractability of hexagonal network model with random user location"
    - "robust methods for lte and wimax dimensioning"
    - "a tractable approach to coverage and rate in cellular networks"

Connected through hyperedge HE-3 (induced by source paper "max min rates in self backhauled millimeter wave cellular networks"):
  with members:
    - "improving the coverage and spectral efficiency of millimeter wave cellular networks using device to device relays"
    - "modeling and analyzing millimeter wave cellular systems"
    - "inter operator resource management for millimeter wave multi hop backhaul networks"
    - "performance of dynamic and static tdd in self backhauled millimeter wave cellular networks"
    - "optimal joint routing and scheduling in millimeter wave cellular networks"
    - "correction factor for analysis of mimo wireless networks with highly directional beamforming"
    - "gbps user rates using mmwave relayed backhaul with high gain antennas"
    - "tractable model for rate in self backhauled millimeter wave cellular networks"

Connected through hyperedge HE-4 (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"
    - "success probability and area spectral efficiency of a vanet modeled as a cox process"
    - "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"

Connected through hyperedge HE-5 (induced by source paper "mmwave beam prediction with situational awareness a machine learning approach"):
  with members:
    - "inverse multipath fingerprinting for millimeter wave v2i beam alignment"
    - "millimeter wave vehicular communication to support massive automotive sensing"

Connected through hyperedge HE-6 (induced by source paper "coverage analysis of a vehicular network modeled as cox process driven by poisson line process"):
  with members:
    - "modeling and analysis of cellular networks using stochastic geometry a tutorial"
    - "asymptotic blind spot analysis of localization networks under correlated blocking using a poisson line process"
    - "a primer on cellular network analysis using stochastic geometry"
    - "a stochastic geometric analysis of device to device communications operating over generalized fading channels"
    - "dual branch mrc receivers under spatial interference correlation and nakagami fading"
    - "modeling and analysis of k tier downlink heterogeneous cellular networks"
    - "random linear multihop relaying in a general field of interferers using spatial aloha"
    - "a tractable approach to coverage and rate in cellular 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.NI(Networking and Internet Architecture)