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: "spectrum and energy efficiency evaluation of two tier femtocell networks with partially open channels"
  Abstract: Two-tier femtocell networks are an efficient communication architecture that significantly improves throughput in indoor environments with low power consumption. Traditionally, a femtocell network is usually configured to be either completely open or completely closed in that its channels are either made available to all users or used by its own users only. This may limit network flexibility and performance. It is desirable for owners of femtocell base stations if a femtocell can partially open its channels for external-user access. In such scenarios, spectrum and energy efficiency becomes a critical issue in the design of femtocell network protocols and structure. In this paper, we conduct performance analysis for two-tier femtocell networks with partially open channels. In particular, we build a Markov chain to model the channel access in the femtocell network and then derive the performance metrics in terms of the blocking probabilities. Based on stationary state probabilities derived by Markov chain models, spectrum and energy efficiency is modeled and analyzed under different scenarios characterized by critical parameters, including number of femtocells in a macrocell, average number of users, and number of open channels in a femtocell. Numerical and Monte Carlo (MC) simulation results indicate that the number of open channels in a femtocell has an adverse impact on the spectrum and energy efficiency of two-tier femtocell networks. Results in this paper provide guidelines for trading off spectrum and energy efficiency of two-tier femtocell networks by configuring different numbers of open channels in a femtocell.

Connected through hyperedge HE-1 (induced by source paper "downlink small cell base station cooperation strategy in fractal small cell networks"):
  with members:
    - "vehicular communications for 5g cooperative small cell networks"
    - "wireless fractal cellular networks"
    - "user mobility evaluation for 5g small cell networks based on individual mobility model"
    - "5g ultra dense cellular networks"
    - "analysis of blockage effects on urban cellular networks"

Connected through hyperedge HE-2 (induced by source paper "system level analysis of heterogeneous networks under imperfect traffic hotspot localization"):
  with members:
    - "analytical tractability of hexagonal network model with random user location"
    - "5g wireless backhaul networks challenges and research advances"
    - "emerging technologies and research challenges for 5g wireless networks"
    - "traffic hotspot localization in 3g and 4g wireless networks using omc metrics"
    - "modeling heterogeneous network interference using poisson point processes"
    - "modeling and analysis of k tier downlink heterogeneous cellular networks"

Connected through hyperedge HE-3 (induced by source paper "mode selection resource allocation and power control for d2d enabled two tier cellular network"):
  with members:
    - "energy efficient resource allocation for device to device underlay communication"
    - "a survey on device to device communication in cellular networks"
    - "spectrum sharing for device to device communication in cellular networks"
    - "distributed resource allocation in device to device enhanced cellular networks"
    - "power control in two tier femtocell networks"

Connected through hyperedge HE-4 (induced by source paper "spatial spectrum and energy efficiency of random cellular networks"):
  with members:
    - "energy efficiency optimization for mimo ofdm mobile multimedia communication systems with qos constraints"
    - "energy efficiency evaluation of cellular networks based on spatial distributions of traffic load and power consumption"
    - "offloading in heterogeneous networks modeling analysis and design insights"
    - "heterogeneous cellular networks with flexible cell association a comprehensive downlink sinr analysis"
    - "a stochastic geometry approach to energy efficiency in relay assisted cellular networks"
    - "modeling and analysis of k tier downlink heterogeneous cellular networks"
    - "green cellular networks a survey some research issues and challenges"
    - "a tractable approach to coverage and rate in cellular networks"

Connected through hyperedge HE-5 (induced by source paper "mobile converged networks framework optimization and challenges"):
  with members:
    - "energy efficiency evaluation of cellular networks based on spatial distributions of traffic load and power consumption"

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)