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: "standalone and non standalone beam management for 3gpp nr at mmwaves"
  Abstract: The next generation of cellular networks will exploit mmWave frequencies to dramatically increase the network capacity. Communication at such high frequencies, however, requires directionality to compensate the increased propagation loss. Users and base stations need to align their beams during both initial access and data transmissions to ensure that the maximum gain is reached. The accuracy of beam selection, and the delay in updating the beam pair or performing initial access, impact the end-to-end performance and the quality of service. In this article we review the beam management procedures included in the 3GPP NR specifications and propose possible enhancements, based on both standalone and non-standalone architectures, to improve network control operations. We also provide a performance comparison among different schemes, along with design insights on the most important parameters related to beam management frameworks.

Connected through hyperedge HE-1 (induced by source paper "a tutorial on beam management for 3gpp nr at mmwave frequencies"):
  with members:
    - "statistical blockage modeling and robustness of beamforming in millimeter wave systems"
    - "adaptive beamwidth selection for contention based access periods in millimeter wave wlans"
    - "study of realistic antenna patterns in 5g mmwave cellular scenarios"
    - "initial access frameworks for 3gpp nr at mmwave frequencies"
    - "on the beamformed broadcast signaling for millimeter wave cell discovery performance analysis and design insight"
    - "caching meets millimeter wave communications for enhanced mobility management in 5g networks"
    - "improved handover through dual connectivity in 5g mmwave mobile networks"
    - "5g millimeter wave cellular system capacity with fully digital beamforming"

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)