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: "how to dimension 5g network when users are distributed on roads modeled by poisson line process"
  Abstract: -The fifth generation (5G) New Radio (NR) interface inherits many concepts and techniques from 4G systems such as the Orthogonal Frequency Division Multiplex (OFDM) based waveform and multiple access. Dimensioning 5G NR interface will likely follow the same principles as in 4G networks. It aims at finding the number of radio resources required to carry a forecast data traffic at a target users Quality of Services (QoS). The present paper attempts to provide a new approach of dimension-ing 5G NR radio resource (number of Physical Resource Blocks) considering its congestion probability, qualified as a relevant metric for QoS evaluation. Moreover, 5G users are assumed to be distributed in roads modeled by Poisson Line Process (PLP) instead of the widely-used 2D-Poisson Point Process. We derive the analytical expression of the congestion probability for analyzing its behavior as a function of network parameters. Then, we set its value, often targeted by the operator, in order to find the relation between the necessary resources and the forecast data traffic expressed in terms of cell throughput. Different numerical results are presented to justify this dimensioning approach.

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"
    - "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"
    - "mmwave vehicle to infrastructure communication analysis of urban microcellular networks"

Connected through hyperedge HE-2 (induced by source paper "statistical blockage modeling and robustness of beamforming in millimeter wave systems"):
  with members:
    - "millimeter wave mimo prototype measurements and experimental results"
    - "small scale local area and transitional millimeter wave propagation for 5g communications"
    - "rapid fading due to human blockage in pedestrian crowds at 5g millimeter wave frequencies"
    - "millimeter wave human blockage at 73 ghz with a simple double knife edge diffraction model and extension for directional antennas"
    - "beamforming tradeoffs for initial ue discovery in millimeter wave mimo systems"
    - "millimeter wave cellular wireless networks potentials and challenges"
    - "spatially sparse precoding in millimeter wave mimo systems"
    - "five disruptive technology directions for 5g"

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)