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: "millimeter wave interference avoidance via building aware associations"
  Abstract: Signal occlusion by building blockages is a double-edged sword for the performance of millimeter-wave (mmW) communication networks. Buildings may dominantly attenuate the useful signals, especially when mmW base stations (BSs) are sparsely deployed compared to the building density. In the opposite BS deployment, buildings can block the undesired interference. To enjoy only the benefit, we propose a building-aware association scheme that adjusts the directional BS association bias of the user equipments (UEs), based on a given building density and the concentration of UE locations around the buildings. The association of each BS can thereby be biased: (i) toward the UEs located against buildings for avoiding interference to other UEs; or (ii) toward the UEs providing their maximum reference signal received powers (RSRPs). The proposed association scheme is optimized to maximize the downlink average data rate derived by stochastic geometry. Its effectiveness is validated by simulation using real building statistics.

Connected through hyperedge HE-1 (induced by source paper "sense and predict harnessing spatial interference correlation for cognitive radio networks"):
  with members:
    - "ultra reliable and low latency communications in 5g downlink physical layer aspects"
    - "the connectivity of millimeter wave networks in urban environments modeled using random lattices"
    - "macro diversity in cellular networks with random blockages"
    - "sense and predict opportunistic mac based on spatial interference correlation for cognitive radio networks"
    - "downlink and uplink cell association with traditional macrocells and millimeter wave small cells"
    - "spatio temporal interference correlation and joint coverage in cellular networks"
    - "design and analysis of initial access in millimeter wave cellular networks"
    - "cognitive random access for internet of things networks"

Connected through hyperedge HE-2 (induced by source paper "lte and millimeter waves for v2i communications an end to end performance comparison"):
  with members:
    - "end to end simulation of 5g mmwave networks"
    - "performance study of lte and mmwave in vehicle to network communications"
    - "coverage and connectivity analysis of millimeter wave vehicular networks"
    - "modeling and design of millimeter wave networks for highway vehicular communication"
    - "millimeter wave vehicular communication to support massive automotive sensing"
    - "performance impact of los and nlos transmissions in dense cellular networks"
    - "millimeter wave cellular wireless networks potentials and challenges"

Connected through hyperedge HE-3 (induced by source paper "stochastic geometric coverage analysis in mmwave cellular networks with realistic channel and antenna radiation models"):
  with members:
    - "study of realistic antenna patterns in 5g mmwave cellular scenarios"
    - "ultra reliable and low latency wireless communication tail risk and scale"
    - "coverage and connectivity analysis of millimeter wave vehicular networks"
    - "modeling and analyzing millimeter wave cellular systems"
    - "coverage analysis for millimeter wave networks the impact of directional antenna arrays"
    - "stochastic geometric coverage analysis in mmwave cellular networks with a realistic channel model"
    - "correction factor for analysis of mimo wireless networks with highly directional beamforming"
    - "revisiting frequency reuse towards supporting ultra reliable ubiquitous rate communication"

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)