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: "user mobility evaluation for 5g small cell networks based on individual mobility model"
  Abstract: Abstract—With small cell networks becoming core parts of the fifth generation (5G) cellular networks, it is an important problem to evaluate the impact of user mobility on 5G small cell networks. However, the tendency and clustering habits in human activities have not been considered in traditional user mobility models. In this paper, human tendency and clustering behaviors are first considered to evaluate the user mobility performance for 5G small cell networks based on individual mobility model (IMM). As key contributions, user pause probability, user arrival and departure probabilities are derived in this paper for evaluating the user mobility performance in a hotspot-type 5G small cell network. Furthermore, coverage probabilities of small cell and macro cell BSs are derived for all users in 5G small cell networks, respectively. Compared with the traditional random waypoint (RWP) model, IMM provides a different viewpoint to investigate the impact of human tendency and clustering behaviors on the performance of 5G small cell networks.

Connected through hyperedge HE-1 (induced by source paper "spatio temporal modeling for massive and sporadic access"):
  with members:
    - "tradeoff between delay and physical layer security in wireless networks"
    - "aggregation and resource scheduling in machine type communication networks a stochastic geometry approach"
    - "random access analysis for massive iot networks under a new spatio temporal model a stochastic geometry approach"
    - "spatiotemporal stochastic modeling of iot enabled cellular networks scalability and stability analysis"
    - "heterogeneous cellular networks with spatio temporal traffic delay analysis and scheduling"
    - "massive machine type communication with data aggregation and resource scheduling"
    - "massive machine type communications in 5g physical and mac layer solutions"
    - "user centric mobility management in ultra dense cellular networks under spatio temporal dynamics"

Connected through hyperedge HE-2 (induced by source paper "an actor critic based uav bss deploymentmethod for dynamic environments"):
  with members:
    - "a tutorial on uavs for wireless networks applications challenges and open problems"
    - "joint trajectory and communication design for multi uav enabled wireless networks"
    - "mobile unmanned aerial vehicles uavs for energy efficient internet of things communications"
    - "heterogeneous cellular networks with spatio temporal traffic delay analysis and scheduling"
    - "wireless communications with unmanned aerial vehicles opportunities and challenges"
    - "spatial spectrum and energy efficiency of random cellular networks"
    - "continuous control with deep reinforcement learning"
    - "energy efficiency evaluation of cellular networks based on spatial distributions of traffic load and power consumption"

Connected through hyperedge HE-3 (induced by source paper "fundamental limits of age of information in stationary and non stationary environments"):
  with members:
    - "on minimizing the maximum age of information for wireless erasure channels"
    - "age of information in multiple sensing of a single source"
    - "age optimal information gathering and dissemination on graphs"
    - "scheduling policies for minimizing age of information in broadcast wireless networks"
    - "on the age of information in status update systems with packet management"

Connected through hyperedge HE-4 (induced by source paper "smart contract based secure spectrum sharing in multi operators wireless communication networks"):
  with members:
    - "smart contract slas for dense small cell as a service"
    - "traffic management for heterogeneous networks with opportunistic unlicensed spectrum sharing"
    - "spatial spectrum and energy efficiency of random cellular networks"
    - "energy efficiency evaluation of cellular networks based on spatial distributions of traffic load and power consumption"
    - "capacity analysis of a multi cell multi antenna cooperative cellular network with co channel interference"

Connected through hyperedge HE-5 (induced by source paper "neural networks in hybrid precoding for millimeter wave massive mimo systems"):
  with members:
    - "deep learning based channel estimation for beamspace mmwave massive mimo systems"
    - "energy efficiency of mmwave massive mimo precoding with low resolution dacs"
    - "an introduction to deep learning for the physical layer"
    - "energy efficiency challenges of 5g small cell networks"
    - "energy efficiency optimization of 5g radio frequency chain systems"
    - "spatial spectrum and energy efficiency of random cellular networks"
    - "deep residual learning for image recognition"
    - "5g ultra dense cellular networks"

Connected through hyperedge HE-6 (induced by source paper "a novel jt comp scheme in 5g fractal small cell networks"):
  with members:
    - "ultra reliable uav communication using altitude and cooperation diversity"
    - "downlink small cell base station cooperation strategy in fractal small cell networks"
    - "wireless fractal cellular networks"
    - "spatial spectrum and energy efficiency of random cellular networks"
    - "5g ultra dense cellular networks"
    - "a stochastic geometry framework for analyzing pairwise cooperative cellular networks"
    - "5g wireless backhaul networks challenges and research advances"
    - "energy efficiency optimization for mimo ofdm mobile multimedia communication systems with qos constraints"

Connected through hyperedge HE-7 (induced by source paper "performance analysis of urban mmwave multi hop v2v communications with shifted exponential distribution headway"):
  with members:
    - "5g software defined vehicular networks"
    - "energy efficiency challenges of 5g small cell networks"
    - "multi hop links quality analysis of 5g enabled vehicular networks"
    - "energy efficiency optimization of 5g radio frequency chain systems"
    - "spatial spectrum and energy efficiency of random cellular networks"
    - "5g ultra dense cellular networks"
    - "5g wireless backhaul networks challenges and research advances"
    - "energy efficiency optimization for mimo ofdm mobile multimedia communication systems with qos constraints"

Connected through hyperedge HE-8 (induced by source paper "energy efficiency of generalized spatial modulation aided massive mimo systems"):
  with members:
    - "machine learning inspired energy efficient hybrid precoding for mmwave massive mimo systems"
    - "energy efficiency challenges of 5g small cell networks"
    - "spatial spectrum and energy efficiency of random cellular networks"
    - "5g ultra dense cellular networks"
    - "5g wireless backhaul networks challenges and research advances"
    - "impact of transceiver power consumption on the energy efficiency of zero forcing detector in massive mimo systems"
    - "what will 5g be"
    - "optimal design of energy efficient multi user mimo systems is massive mimo the answer"

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)