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: "on spectrum sharing among micro operators in 5g"
  Abstract: The growing demand in indoor small cell networks has given rise to the concept of micro-operators (MOs) for local service delivery. We model and analyze a spectrum sharing system involving such MOs where a buyer MO buys multiple licensed subbands provided by the regulator. Also, all small cell base stations (SBSs) owned by a buyer MO can utilize multiple licensed subbands at the same time which are also used by other MOs. A deterministic model in which the location of the SBSs are known can lead to unwieldy problem formulation, when the number of SBSs is large. Subsequently, we adopt a stochastic geometric model of the SBS deployment instead of a deterministic model. Assuming that the locations of the SBSs can be modeled as a homogeneous Poisson point process, we find the downlink signal-to-interference-plus-noise ratio (SINR) coverage probability and average data rate for a typical user (UE) served by the buyer MO in a spectrum sharing environment. In order to satisfy the QoS constraint, we provide a greedy algorithm to find how many licensed subbands and which subband for the buyer MO to purchase from the regulator. We also derive the coverage probability of the buyer MO for interference the limited system.

Connected through hyperedge HE-1 (induced by source paper "iris deep reinforcement learning driven shared spectrum access architecture for indoor neutral host small cells"):
  with members:
    - "deepmind control suite"
    - "shared spectrum access communications a neutral host micro operator approach"
    - "multi agent actor critic for mixed cooperative competitive environments"
    - "deep reinforcement learning for robotic manipulation with asynchronous off policy updates"
    - "resource allocation in shared spectrum access communications for operators with diverse service requirements"
    - "benchmarking deep reinforcement learning for continuous control"
    - "high dimensional continuous control using generalized advantage estimation"
    - "co primary inter operator spectrum sharing over a limited spectrum pool using repeated games"

Connected through hyperedge HE-2 (induced by source paper "infrastructure sharing for mobile network operators analysis of trade offs and market"):
  with members:
    - "inter operator infrastructure sharing trade offs and market"
    - "designing and implementing future aerial communication networks"
    - "on spectrum and infrastructure sharing in multi operator cellular networks"
    - "integral approximations for coverage probability"
    - "soaran a service oriented architecture for radio access network sharing in evolving mobile networks"
    - "a tractable approach to coverage and rate in cellular networks"

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)