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 the network layer modeling and configuration of programmable wireless environments"
  Abstract: Programmable wireless environments enable the software-defined propagation of waves within them, yielding exceptional performance. Several building-block technologies have been implemented and evaluated at the physical layer in the past. The present work contributes a network-layer solution to configure such environments for multiple users and objectives, and for any underlying physical-layer technology. Supported objectives include any combination of Quality of Service and power transfer optimization, eavesdropping, and Doppler effect mitigation, in multi-cast or uni-cast settings. In addition, a graph-based model of programmable environments is proposed, which incorporates core physical observations and efficiently separates physical and networking concerns. The evaluation takes place in a specially developed simulation tool, and in a variety of environments, validating the model and reaching insights into the user capacity of programmable environments.

Connected through hyperedge HE-1 (induced by source paper "an interpretable neural network for configuring programmable wireless environments"):
  with members:
    - "a novel communication paradigm for high capacity and security via programmable indoor wireless environments in next generation wireless systems"
    - "energy efficient multi user miso communication using low resolution large intelligent surfaces"
    - "using any surface to realize a new paradigm for wireless communications"
    - "beyond massive mimo the potential of data transmission with large intelligent surfaces"
    - "beamforming optimization for intelligent reflecting surface with discrete phase shifts"
    - "intelligent reflecting surface enhanced wireless network joint active and passive beamforming design"
    - "efficient processing of deep neural networks a tutorial and survey"

Connected through hyperedge HE-2 (induced by source paper "rfocus practical beamforming for small devices"):
  with members:
    - "a novel communication paradigm for high capacity and security via programmable indoor wireless environments in next generation wireless systems"
    - "reflection probability in wireless networks with metasurface coated environmental objects an approach based on random spatial processes"

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)