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: "rfocus practical beamforming for small devices"
  Abstract: To reduce transmit power, increase throughput, and improve communication range, radio systems---such as IoT sensor networks, Wi-Fi and cellular networks---benefit from the ability to direct their signals, to ensure that more of the transmitted power reaches the receiver. Many modern systems beamform with antenna arrays for this purpose. However, a radio's ability to direct its signal is fundamentally limited by its size. Unfortunately practical challenges limit the size of modern radios, and consequently, their ability to beamform. In many settings, radios on devices must be small and inexpensive; today, these settings are unable to benefit from high-precision beamforming. #R##N#To address this problem, we introduce RFocus, which moves beamforming functions from the radio endpoints to the environment. RFocus includes a two-dimensional surface with a rectangular array of simple elements, each of which functions as an RF switch. Each element either lets the signal through or reflects it. The surface does not emit any power of its own. The state of the elements is set by a software controller to maximize the signal strength at a receiver, with a novel optimization algorithm that uses signal strength measurements from the receiver. The RFocus surface can be manufactured as an inexpensive thin wallpaper, requiring no wiring. This solution requires only a method to communicate received signal strengths periodically to the RFocus controller. Our prototype implementation improves the median signal strength by 10.5x, and the median channel capacity by 2.1x.

Connected through hyperedge HE-1 (induced by source paper "overhead aware design of reconfigurable intelligent surfaces in smart radio environments"):
  with members:
    - "over the air computation via intelligent reflecting surfaces"
    - "holographic mimo surfaces for 6g wireless networks opportunities challenges and trends"
    - "intelligent reflecting surface with discrete phase shifts channel estimation and passive beamforming"
    - "miso wireless communication systems via intelligent reflecting surfaces"
    - "secure wireless communication via intelligent reflecting surface"
    - "joint active and passive beamforming for intelligent reflecting surface assisted massive mimo systems"
    - "cascaded channel estimation for large intelligent metasurface assisted massive mimo"
    - "intelligent reflecting surface irs enabled covert communications in wireless networks"

Connected through hyperedge HE-2 (induced by source paper "asymptotic max min sinr analysis of reconfigurable intelligent surface assisted miso systems"):
  with members:
    - "intelligent reflecting surface versus decode and forward how large surfaces are needed to beat relaying"
    - "large intelligent surface antennas lisa making reflective radios smart"
    - "asymptotic analysis of rzf over double scattering channels with mmse estimation"
    - "resource allocation for secure irs assisted multiuser miso systems"
    - "enabling secure wireless communications via intelligent reflecting surfaces"
    - "enabling large intelligent surfaces with compressive sensing and deep learning"
    - "mimo assisted networks relying on large intelligent surfaces a stochastic geometry model"
    - "towards smart and reconfigurable environment intelligent reflecting surface aided wireless network"

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)