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: "r fft function split at ifft fft in unified lte cran and cable access network"
  Abstract: The remote-PHY (R-PHY) modular cable network for data over cable service interface specification (DOCSIS) service conducts the physical layer processing for the transmissions over the broadcast cable in a remote node. In contrast, the cloud radio access network (CRAN) for long-term evolution (LTE) cellular wireless services conducts all baseband physical layer processing in a central baseband unit and the remaining physical layer processing steps toward radio frequency (RF) transmission in remote nodes. Both DOCSIS and LTE are based on orthogonal frequency division multiplexing physical layer processing. We propose to unify cable and wireless cellular access networks by utilizing the hybrid fiber-coax (HFC) cable network infrastructure as fiber fronthaul network for cellular wireless services. For efficient operation of such a unified access network, we propose a novel remote-fast-Fourier transform (R-FFT) node that conducts the physical layer processing from the FFT module toward the RF transmission, whereby DOCSIS and LTE share a common FFT module. The frequency domain in-phase and quadrature (I/Q) symbols for both DOCSIS and LTE are transmitted over the fiber between remote node and cable headend, where the remaining physical layer processing is conducted. We further propose to cache repetitive quadrature amplitude modulation (QAM) symbols in the R-FFT node to reduce the fronthaul bitrate requirements and enable statistical multiplexing. We evaluate the fronthaul bitrate reductions achieved by R-FFT node caching, the fronthaul transmission bitrates arising from the unified DOCSIS and LTE service, and illustrate the delay implications of moving part of the cable R-PHY remote node physical layer processing to the headend. Overall, our evaluations indicate that the proposed R-FFT node can effectively support unified DOCSIS and LTE services over the HFC cable plant while substantially reducing the fronthaul bitrate requirements of the existing CRAN structures.

Connected through hyperedge HE-1 (induced by source paper "ultra low latency ull networks the ieee tsn and ietf detnet standards and related 5g ull research"):
  with members:
    - "a basic result on the superposition of arrival processes in deterministic networks"
    - "end to end simulation of 5g mmwave networks"
    - "information and communications technologies for sustainable development goals state of the art needs and perspectives"
    - "5g fronthaul latency and jitter studies of cpri over ethernet"
    - "towards 5g enabled tactile robotic telesurgery"
    - "fog aided wireless networks for content delivery fundamental latency tradeoffs"
    - "formal scheduling constraints for time sensitive networks"
    - "business case and technology analysis for 5g low latency applications"

Connected through hyperedge HE-2 (induced by source paper "latency bounds of packet based fronthaul for cloud ran with functionality split"):
  with members:
    - "approximations and bounds for n k fork join queues a linear transformation approach"
    - "reliable and low latency fronthaul for tactile internet applications"
    - "coding for fast content download"

Connected through hyperedge HE-3 (induced by source paper "a survey on low latency towards 5g ran core network and caching solutions"):
  with members:
    - "stochastic optimization and control framework for 5g network slicing with effective isolation"
    - "ultra reliable and low latency communications in 5g downlink physical layer aspects"
    - "human in the loop wireless communications machine learning and brain aware resource management"
    - "a survey on mobile edge networks convergence of computing caching and communications"
    - "joint user association power control and scheduling in multi cell 5g networks"
    - "fundamental limits on latency in transceiver cache aided hetnets"
    - "decentralized coded caching in wireless networks trade off between storage and latency"
    - "provisioning low latency resilient mobile edge clouds for 5g"

Connected through hyperedge HE-4 (induced by source paper "will sdn be part of 5g"):
  with members:
    - "5g fronthaul latency and jitter studies of cpri over ethernet"
    - "nfv and sdn key technology enablers for 5g networks"
    - "hardware accelerated sdr platform for adaptive air interfaces"
    - "srslte an open source platform for lte evolution and experimentation"
    - "software defined optical networks sdons a comprehensive survey"
    - "cross layer software defined 5g network"
    - "are heterogeneous cloud based radio access networks cost effective"
    - "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.NI(Networking and Internet Architecture)