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: "urllc embb slicing to support vr multimodal perceptions over wireless cellular systems"
  Abstract: Virtual reality (VR) enables mobile wireless users to experience multimodal perceptions in a virtual space. In this paper we investigate the problem of concurrent support of visual and haptic perceptions over wireless cellular networks, with a focus on the downlink transmission phase. While the visual perception requires moderate reliability and maximized rate, the haptic perception requires fixed rate and high reliability. Hence, the visuo-haptic VR traffic necessitates the use of two different network slices: enhanced mobile broadband (eMBB) for visual perception and ultra-reliable and low latency communication (URLLC) for haptic perception. We investigate two methods by which these two slices share the downlink resources orthogonally and non-orthogonally, respectively. We compare these methods in terms of the just-noticeable difference (JND), an established measure in psychophysics, and show that non-orthogonal slicing becomes preferable under a higher target integrated-perceptual resolution and/or a higher target rate for haptic perceptions.

Connected through hyperedge HE-1 (induced by source paper "intelligent resource slicing for embb and urllc coexistence in 5g and beyond a deep reinforcement learning based approach"):
  with members:
    - "extreme urllc vision challenges and key enablers"
    - "coexistence mechanism between embb and urllc in 5g wireless networks"
    - "embb urllc resource slicing a risk sensitive approach"
    - "ultra reliable and low latency vehicular transmission an extreme value theory approach"
    - "ultra reliable and low latency wireless communication tail risk and scale"
    - "coexistence of urllc and embb services in the c ran uplink an information theoretic study"
    - "5g wireless network slicing for embb urllc and mmtc a communication theoretic view"
    - "ultra reliable and low latency communications in 5g downlink physical layer aspects"

Connected through hyperedge HE-2 (induced by source paper "multicast embb and bursty urllc service multiplexing in a comp enabled ran"):
  with members:
    - "ran slicing for massive iot and bursty urllc service multiplexing analysis and optimization"
    - "embb urllc resource slicing a risk sensitive approach"
    - "harmonizing 3gpp and nfv description models providing customized ran slices in 5g networks"
    - "resource allocation and harq optimization for urllc traffic in 5g wireless networks"
    - "5g wireless network slicing for embb urllc and mmtc a communication theoretic view"
    - "non orthogonal embb urllc radio access for cloud radio access networks with analog fronthauling"
    - "network slicing to enable scalability and flexibility in 5g mobile networks"
    - "sample approximation based deflation approaches for chance sinr constrained joint power and admission control"

Connected through hyperedge HE-3 (induced by source paper "risk based optimization of virtual reality over terahertz reconfigurable intelligent surfaces"):
  with members:
    - "on the reliability of wireless virtual reality at terahertz thz frequencies"
    - "a vision of 6g wireless systems applications trends technologies and open research problems"
    - "reconfigurable intelligent surfaces for energy efficiency in wireless communication"
    - "human in the loop wireless communications machine learning and brain aware resource management"
    - "virtual reality over wireless networks quality of service model and learning based resource management"
    - "rl 2 fast reinforcement learning via slow reinforcement learning"
    - "artificial neural networks based machine learning for wireless networks a tutorial"
    - "software defined network controlled switching between millimeter wave and terahertz small cells"

Connected through hyperedge HE-4 (induced by source paper "extreme urllc vision challenges and key enablers"):
  with members:
    - "ultra reliable and low latency vehicular communication an active learning approach"
    - "massive autonomous uav path planning a neural network based mean field game theoretic approach"
    - "one pixel image and rf signal based split learning for mmwave received power prediction"
    - "time synchronization in 5g wireless edge requirements and solutions for critical mtc"
    - "a vision of 6g wireless systems applications trends technologies and open research problems"
    - "wireless network intelligence at the edge"
    - "a statistical learning approach to ultra reliable low latency communication"

Connected through hyperedge HE-5 (induced by source paper "wireless edge computing with latency and reliability guarantees"):
  with members:
    - "distributed federated learning for ultra reliable low latency vehicular communications"
    - "machine learning at the wireless edge distributed stochastic gradient descent over the air"
    - "how reliable and capable is multi connectivity"
    - "a tutorial on beam management for 3gpp nr at mmwave frequencies"
    - "uav communications for 5g and beyond recent advances and future trends"
    - "coded federated computing in wireless networks with straggling devices and imperfect csi"
    - "ultra reliable communication in 5g mmwave networks a risk sensitive approach"
    - "on device federated learning via blockchain and its latency analysis"

Connected through hyperedge HE-6 (induced by source paper "towards tactile internet in beyond 5g era recent advances current issues and future directions"):
  with members:
    - "emerging edge computing technologies for distributed iot systems"
    - "the effect of iot new features on security and privacy new threats existing solutions and challenges yet to be solved"
    - "ultrareliable and low latency communication techniques for tactile internet services"
    - "scalable intelligence enabled networking with traffic engineering in 5g scenarios for future audio visual tactile internet"
    - "distributed optimization for energy efficient fog computing in the tactile internet"
    - "joint uplink and downlink resource configuration for ultra reliable and low latency communications"
    - "robust multi path communications for uavs in the urban iot"
    - "a d2d based protocol for ultra reliable wireless communications for industrial automation"

Connected through hyperedge HE-7 (induced by source paper "data correlation aware resource management in wireless virtual reality vr an echo state transfer learning approach"):
  with members:
    - "cache placement in two tier hetnets with limited storage capacity cache or buffer"
    - "communication computing and caching for mobile vr delivery modeling and trade off"
    - "edge computing meets millimeter wave enabled vr paving the way to cutting the cord"
    - "human in the loop wireless communications machine learning and brain aware resource management"
    - "virtual reality over wireless networks quality of service model and learning based resource management"
    - "echo state transfer learning for data correlation aware resource allocation in wireless virtual reality"
    - "proactive resource management for lte in unlicensed spectrum a deep learning perspective"
    - "caching in the sky proactive deployment of cache enabled unmanned aerial vehicles for optimized quality of experience"

Connected through hyperedge HE-8 (induced by source paper "a vision of 6g wireless systems applications trends technologies and open research problems"):
  with members:
    - "beyond 5g with uavs foundations of a 3d wireless cellular network"
    - "wireless network intelligence at the edge"
    - "ultra reliable and low latency wireless communication tail risk and scale"
    - "beyond massive mimo the potential of data transmission with large intelligent surfaces"
    - "propagation measurement system and approach at 140 ghz moving to 6g and above 100 ghz"
    - "human in the loop wireless communications machine learning and brain aware resource management"
    - "virtual reality over wireless networks quality of service model and learning based resource management"
    - "artificial neural networks based machine learning for wireless networks a tutorial"

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)