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: "a new vehicle localization scheme based on combined optical camera communication and photogrammetry"
  Abstract: The demand for autonomous vehicles is increasing gradually owing to their enormous potential benefits. However, several challenges, such as vehicle localization, are involved in the development of autonomous vehicles. A simple and secure algorithm for vehicle positioning is proposed herein without massively modifying the existing transportation infrastructure. For vehicle localization, vehicles on the road are classified into two categories: host vehicles (HVs) are the ones used to estimate other vehicles’ positions and forwarding vehicles (FVs) are the ones that move in front of the HVs. The FV transmits modulated data from the tail (or back) light, and the camera of the HV receives that signal using optical camera communication (OCC). In addition, the streetlight (SL) data are considered to ensure the position accuracy of the HV. Determining the HV position minimizes the relative position variation between the HV and FV. Using photogrammetry, the distance between FV or SL and the camera of the HV is calculated by measuring the occupied image area on the image sensor. Comparing the change in distance between HV and SLs with the change in distance between HV and FV, the positions of FVs are determined. The performance of the proposed technique is analyzed, and the results indicate a significant improvement in performance. The experimental distance measurement validated the feasibility of the proposed scheme.

Connected through hyperedge HE-1 (induced by source paper "6g wireless communication systems applications requirements technologies challenges and research directions"):
  with members:
    - "towards 6g networks use cases and technologies"
    - "blockchain for internet of things a survey"
    - "uav communications for 5g and beyond recent advances and future trends"
    - "a vision of 6g wireless systems applications trends technologies and open research problems"
    - "on the effect of temporal correlation on joint success probability and distribution of number of interferers in mobile uav networks"
    - "six key enablers for machine type communication in 6g"
    - "integrated rf optical wireless networks for improving qos in indoor and transportation applications"
    - "a speculative study on 6g"

Connected through hyperedge HE-2 (induced by source paper "integrated rf optical wireless networks for improving qos in indoor and transportation applications"):
  with members:
    - "game based approach for qos provisioning and interference management in heterogeneous networks"
    - "a comparative survey of optical wireless technologies architectures and applications"
    - "handover management in high dense femtocellular networks"
    - "cost effective frequency planning for capacity enhancement of femtocellular networks"

Connected through hyperedge HE-3 (induced by source paper "an implementation approach and performance analysis of image sensor based multilateral indoor localization and navigation system"):
  with members:
    - "a comparative survey of optical wireless technologies architectures and applications"
    - "modern wlan fingerprinting indoor positioning methods and deployment challenges"
    - "csi based fingerprinting for indoor localization a deep learning approach"

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)