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: "resource allocation in noma based fog radio access networks"
  Abstract: In the wake of growth in intelligent mobile devices and wide usage of bandwidth-hungry applications of mobile Internet, the demand of wireless data traffic and ubiquitous mobile broadband is rapidly increasing. On account of these developments, the research on fifth generation (5G) networks presents an accelerative tendency on a global scale. Edge computing draw lots of attention for reducing the time delay and improving the Quality of Service for the networks. While, fog radio access networks (F-RANs) is an emergent architecture, which takes full use of edge computing and distributed storing capabilities in edge devices. In this article, we propose an architecture of non-orthogonal multiple access (NOMA) based F-RANs, which has a strong capability of edge computing and can meet the heterogeneous requirements in 5G systems. NOMA with successive interference cancellation (SIC) is regarded as a critical multi-user access technology. In NOMA, more than one user can access the same time, code domain, and frequency resources. With assigning different power levels to multi-user and implementing SIC, multiple users detection can be achieved. In this article, we provide a description of the NOMA based F-RANs architecture, and discuss the resource allocation in that. We will focus on the power and subchannel allocation in consideration of using NOMA and the edge caching. Simulation results show that the proposed NOMA baesd F-RANs architecture and the resource management mechanisms can achieve the high net utility for the RANs.

Connected through hyperedge HE-1 (induced by source paper "fog aided device to device networks with opportunistic content delivery"):
  with members:
    - "fog radio access networks mobility management interference mitigation and resource optimization"
    - "d2d aware device caching in mmwave cellular networks"
    - "spatially correlated content caching for device to device communications"
    - "caching in the sky proactive deployment of cache enabled unmanned aerial vehicles for optimized quality of experience"
    - "fog computing based radio access networks issues and challenges"
    - "the three primary colors of mobile systems"
    - "mobility aware caching in d2d networks"
    - "wireless content caching for small cell and d2d networks"

Connected through hyperedge HE-2 (induced by source paper "efficient resource allocation for mobile edge computing networks with noma completion time and energy minimization"):
  with members:
    - "a vision of 6g wireless systems applications trends technologies and open research problems"
    - "a survey of multi access edge computing in 5g and beyond fundamentals technology integration and state of the art"
    - "interplay between noma and other emerging technologies a survey"
    - "joint power and time allocation for noma mec offloading"
    - "delay minimization for noma mec offloading"
    - "edge computing aware noma for 5g networks"
    - "impact of non orthogonal multiple access on the offloading of mobile edge computing"
    - "a survey on mobile edge computing the communication perspective"

Connected through hyperedge HE-3 (induced by source paper "power allocation in cache aided noma systems optimization and deep reinforcement learning approaches"):
  with members:
    - "non orthogonal multiple access common myths and critical questions"
    - "joint power allocation and beamforming for non orthogonal multiple access noma in 5g millimeter wave communications"
    - "on optimal power allocation for downlink non orthogonal multiple access systems"
    - "noma assisted wireless caching strategies and performance analysis"
    - "a survey of downlink non orthogonal multiple access for 5g wireless communication networks"
    - "non orthogonal multiple access in multi cell networks theory performance and practical challenges"
    - "adam a method for stochastic optimization"
    - "fundamental limits of caching in wireless d2d networks"

Connected through hyperedge HE-4 (induced by source paper "interference management in noma based fog radio access networks via joint scheduling and power adaptation"):
  with members:
    - "power domain non orthogonal multiple access noma in 5g systems potentials and challenges"
    - "fog computing based radio access networks issues and challenges"
    - "fronthaul constrained cloud radio access networks insights and challenges"
    - "on the performance of non orthogonal multiple access in 5g systems with randomly deployed users"

Connected through hyperedge HE-5 (induced by source paper "reinforcement learning based resource allocation in fog ran for iot with heterogeneous latency requirements"):
  with members:
    - "optimizing the number of fog nodes for cloud fog thing networks"
    - "a survey on mobile edge networks convergence of computing caching and communications"
    - "recent advances in fog radio access networks performance analysis and radio resource allocation"
    - "recent advances in cloud radio access networks system architectures key techniques and open issues"
    - "learning how to communicate in the internet of things finite resources and heterogeneity"
    - "joint optimization of cloud and edge processing for fog radio access networks"
    - "cluster content caching an energy efficient approach to improve quality of service in cloud radio access networks"
    - "fronthaul constrained cloud radio access networks insights 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.IT(Information Theory)