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: "v2x meets noma non orthogonal multiple access for 5g enabled vehicular networks"
  Abstract: Benefited from the widely deployed infrastructure, the LTE network has recently been considered as a promising candidate to support the vehicle-to-everything (V2X) services. However, with a massive number of devices accessing the V2X network in the future, the conventional OFDM-based LTE network faces the congestion issues due to its low efficiency of orthogonal access, resulting in significant access delay and posing a great challenge especially to safety-critical applications. The non-orthogonal multiple access (NOMA) technique has been well recognized as an effective solution for the future 5G cellular networks to provide broadband communications and massive connectivity. In this article, we investigate the applicability of NOMA in supporting cellular V2X services to achieve low latency and high reliability. Starting with a basic V2X unicast system, a novel NOMA-based scheme is proposed to tackle the technical hurdles in designing high spectral efficient scheduling and resource allocation schemes in the ultra dense topology. We then extend it to a more general V2X broadcasting system. Other NOMA-based extended V2X applications and some open issues are also discussed.

Connected through hyperedge HE-1 (induced by source paper "a survey of rate optimal power domain noma schemes for enabling technologies of future wireless networks"):
  with members:
    - "generalized coordinated multipoint gcomp enabled noma outage capacity and power allocation"
    - "what role can noma play in massive mimo"
    - "uav data collection over noma backscatter networks uav altitude and trajectory optimization"
    - "uav communications for 5g and beyond recent advances and future trends"
    - "when full duplex wireless meets non orthogonal multiple access opportunities and challenges"
    - "on optimizing vlc networks for downlink multi user transmission a survey"
    - "beam design and user scheduling for nonorthogonal multiple access with multiple antennas based on pareto optimality"
    - "spatial modulation assisted multi antenna non orthogonal multiple access"

Connected through hyperedge HE-2 (induced by source paper "otfs noma an efficient approach for exploiting heterogenous user mobility profiles"):
  with members:
    - "on the diversity of uncoded otfs modulation in doubly dispersive channels"
    - "on the diversity of otfs modulation in doubly dispersive channels"
    - "mimo otfs in high doppler fading channels signal detection and channel estimation"
    - "otfs a new generation of modulation addressing the challenges of 5g"
    - "on otfs modulation for high doppler fading channels"
    - "interference cancellation and iterative detection for orthogonal time frequency space modulation"
    - "impact of non orthogonal multiple access on the offloading of mobile edge computing"
    - "nr wide bandwidth operations"

Connected through hyperedge HE-3 (induced by source paper "network slicing for vehicular communication"):
  with members:
    - "ultra reliable and low latency wireless communication tail risk and scale"
    - "on the application of network slicing for 5g v2x"
    - "network slicing to enable scalability and flexibility in 5g mobile networks"
    - "software defined networking a comprehensive survey"
    - "a tutorial on spectral clustering"

Connected through hyperedge HE-4 (induced by source paper "blind signal classification for non orthogonal multiple access in vehicular networks"):
  with members:
    - "blind signal classification analysis and impact on user scheduling and power allocation in nonorthogonal multiple access"
    - "bi directional cooperative noma without full csit"
    - "deep learning models for wireless signal classification with distributed low cost spectrum sensors"
    - "power domain non orthogonal multiple access noma in 5g systems potentials and challenges"
    - "deep architectures for modulation recognition"
    - "noma based calibration for large scale spaceborne antenna arrays"
    - "a general mimo framework for noma downlink and uplink transmission based on signal alignment"
    - "on the performance of non orthogonal multiple access in 5g systems with randomly deployed users"

Connected through hyperedge HE-5 (induced by source paper "blind signal classification for non orthogonal multiple access in internet of things networks"):
  with members:
    - "bi directional cooperative noma without full csit"
    - "deep learning models for wireless signal classification with distributed low cost spectrum sensors"
    - "deep architectures for modulation recognition"
    - "noma based calibration for large scale spaceborne antenna arrays"
    - "a general mimo framework for noma downlink and uplink transmission based on signal alignment"

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.IT(Information Theory)