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: "energy efficiency evaluation of cellular networks based on spatial distributions of traffic load and power consumption"
  Abstract: Energy efficiency has gained its significance when service providers' operational costs burden with the rapidly growing data traffic demand in cellular networks. In this paper, we propose an energy efficiency model for Poisson-Voronoi tessellation (PVT) cellular networks considering spatial distributions of traffic load and power consumption. The spatial distributions of traffic load and power consumption are derived for a typical PVT cell, and can be directly extended to the whole PVT cellular network based on the Palm theory. Furthermore, the energy efficiency of PVT cellular networks is evaluated by taking into account traffic load characteristics, wireless channel effects and interference. Both numerical and Monte Carlo simulations are conducted to evaluate the performance of the energy efficiency model in PVT cellular networks. These simulation results demonstrate that there exist maximal limits for energy efficiency in PVT cellular networks for given wireless channel conditions and user intensity in a cell.

Connected through hyperedge HE-1 (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"
    - "user mobility evaluation for 5g small cell networks based on individual mobility model"
    - "continuous control with deep reinforcement learning"

Connected through hyperedge HE-2 (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"
    - "user mobility evaluation for 5g small cell networks based on individual mobility model"
    - "capacity analysis of a multi cell multi antenna cooperative cellular network with co channel interference"

Connected through hyperedge HE-3 (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"
    - "user mobility evaluation for 5g small cell networks based on individual mobility model"
    - "deep residual learning for image recognition"

Connected through hyperedge HE-4 (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"
    - "user mobility evaluation for 5g small cell networks based on individual mobility model"
    - "5g ultra dense cellular networks"
    - "a stochastic geometry framework for analyzing pairwise cooperative cellular networks"
    - "5g wireless backhaul networks challenges and research advances"

Connected through hyperedge HE-5 (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"
    - "user mobility evaluation for 5g small cell networks based on individual mobility model"
    - "5g ultra dense cellular networks"
    - "5g wireless backhaul networks challenges and research advances"

Connected through hyperedge HE-6 (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"
    - "user mobility evaluation for 5g small cell networks based on individual mobility model"
    - "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"

Connected through hyperedge HE-7 (induced by source paper "ultra reliable low latency communications in autonomous vehicular networks"):
  with members:
    - "joint optimization of computation and communication power in multi user massive mimo systems"
    - "coverage and handoff analysis of 5g fractal small cell networks"
    - "5g software defined vehicular networks"
    - "software defined space air ground integrated vehicular networks challenges and solutions"
    - "network slicing to enable scalability and flexibility in 5g mobile networks"
    - "dense small cell networks from noise limited to dense interference limited"
    - "vehicular communications for 5g cooperative small cell networks"
    - "heterogeneous cellular networks with spatio temporal traffic delay analysis and scheduling"

Connected through hyperedge HE-8 (induced by source paper "a new small world iot routing mechanism based on cayley graphs"):
  with members:
    - "ultra reliable low latency communications in autonomous vehicular networks"
    - "tradeoff between delay and physical layer security in wireless networks"
    - "joint optimization of computation and communication power in multi user massive mimo systems"
    - "coverage and handoff analysis of 5g fractal small cell networks"
    - "cache aided non orthogonal multiple access"
    - "toward a tractable delay analysis in ultra dense networks"
    - "capacity analysis of a multi cell multi antenna cooperative cellular network with co channel interference"
    - "throughput delay reliability tradeoff with arq in wireless ad hoc networks"

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)