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: "performance study of lte and mmwave in vehicle to network communications"
  Abstract: A key enabler for the emerging autonomous and cooperative driving services is high-throughput and reliable Vehicle-to-Network (V2N) communication. In this respect, the millimeter wave (mmWave) frequencies hold great promises because of the large available bandwidth which may provide the required link capacity. However, this potential is hindered by the challenging propagation characteristics of high-frequency channels and the dynamic topology of the vehicular scenarios, which affect the reliability of the connection. Moreover, mmWave transmissions typically leverage beamforming gain to compensate for the increased path loss experienced at high frequencies. This, however, requires fine alignment of the transmitting and receiving beams, which may be difficult in vehicular scenarios. Those limitations may undermine the performance of V2N communications and pose new challenges for proper vehicular communication design. In this paper, we study by simulation the practical feasibility of some mmWave-aware strategies to support V2N, in comparison to the traditional LTE connectivity below 6 GHz. The results show that the orchestration among different radios represents a viable solution to enable both high-capacity and robust V2N communications.

Connected through hyperedge HE-1 (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"
    - "coverage and connectivity analysis of millimeter wave vehicular networks"
    - "millimeter wave interference avoidance via building aware associations"
    - "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-2 (induced by source paper "investigating value of information in future vehicular communications"):
  with members:
    - "on the feasibility of integrating mmwave and ieee 802 11p for v2v communications"
    - "millimeter wave vehicular communication to support massive automotive sensing"

Connected through hyperedge HE-3 (induced by source paper "on the feasibility of integrating mmwave and ieee 802 11p for v2v communications"):
  with members:
    - "coverage and connectivity analysis of millimeter wave vehicular networks"
    - "millimeter wave v2v communications distributed association and beam alignment"
    - "modeling and design of millimeter wave networks for highway vehicular communication"
    - "millimeter wave vehicular communication to support massive automotive sensing"
    - "towards an appropriate receiver beamforming scheme for millimeter wave communication a power consumption based comparison"
    - "modeling the evolution of line of sight blockage for v2v channels"
    - "millimeter wave cellular wireless networks potentials and challenges"

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)