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: "control data separation across edge and cloud for uplink communications in c ran"
  Abstract: Fronthaul limitations in terms of capacity and latency motivate the growing interest in the wireless industry for the study of alternative functional splits between cloud and edge nodes in Cloud Radio Access Network (C-RAN). This work contributes to this line of work by investigating the optimal functional split of control and data plane functionalities at the edge nodes and at the Remote Cloud Center (RCC) as a function of the fronthaul latency. The model under study consists of a two-user time-varying uplink channel in which the RCC has global but delayed channel state information (CSI) due to fronthaul latency, while edge nodes have local but timely CSI. Adopting the adaptive sum-rate as the performance criterion, functional splits whereby the control functionality of rate selection and the decoding of the data-plane frames are carried out at either the edge nodes or at the RCC are compared through analysis and numerical results.

Connected through hyperedge HE-1 (induced by source paper "control data separation with decentralized edge control in fog assisted uplink communications"):
  with members:
    - "fog aided wireless networks for content delivery fundamental latency tradeoffs"
    - "network slicing to enable scalability and flexibility in 5g mobile networks"
    - "cloud radio access network virtualizing wireless access for dense heterogeneous systems"
    - "inter layer per mobile optimization of cloud mobile computing a message passing approach"
    - "distributed rate adaptation and power control in fading multiple access channels"

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)