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: "system level analysis of heterogeneous networks under imperfect traffic hotspot localization"
  Abstract: We study, in this paper, the impact of imperfect small cell positioning with respect to traffic hotspots in cellular networks. In order to derive the throughput distribution in macro and small cells, we firstly perform static level analysis of the system considering a non-uniform distribution of user locations. We secondly introduce the dynamics of the system, characterized by random arrivals and departures of users after a finite service duration, with the service rates and distribution of radio conditions outfitted from the first part of the work. When dealing with the dynamics of the system, macro and small cells are modeled by multi-class processor sharing queues. Macro and small cells are assumed to be operating in the same bandwidth. Consequently, they are coupled due to the mutual interferences generated by each cell to the other. We derive several performance metrics such as the mean flow throughput and the gain, if any, generated from deploying small cells to manage traffic hotspots. Our results show that in case the hotspot is near the macro BS (Base Station), even a perfect positioning of the small cell will not yield improved performance due to the high interference experienced at macro and small cell users. However, in case the hotspot is located far enough from the macro BS, performing errors in small cell positioning is tolerated (since related results show positive gains) and it is still beneficial in offloading traffic from the congested macrocell. The best performance metrics depend also on several other important factors such as the users' arrival intensity, the capacity of the cell and the size of the traffic hotspot

Connected through hyperedge HE-1 (induced by source paper "coverage in downlink heterogeneous mmwave cellular networks with user centric small cell deployment"):
  with members:
    - "3gpp inspired hetnet model using poisson cluster process sum product functionals and downlink coverage"
    - "modeling and analyzing millimeter wave cellular systems"
    - "coverage analysis for millimeter wave networks the impact of directional antenna arrays"
    - "on the energy efficient deployment for ultra dense heterogeneous networks with nlos and los transmissions"
    - "stochastic geometric coverage analysis in mmwave cellular networks with a realistic channel model"
    - "poisson cluster process bridging the gap between ppp and 3gpp hetnet models"
    - "dense small cell networks from noise limited to dense interference limited"
    - "enriched k tier hetnet model to enable the analysis of user centric small cell deployments"

Connected through hyperedge HE-2 (induced by source paper "enriched k tier hetnet model to enable the analysis of user centric small cell deployments"):
  with members:
    - "modeling and analysis of cellular networks using stochastic geometry a tutorial"
    - "a primer on cellular network analysis using stochastic geometry"
    - "fundamentals of cluster centric content placement in cache enabled device to device networks"
    - "poisson cluster process based analysis of hetnets with correlated user and base station locations"
    - "poisson hole process theory and applications to wireless networks"
    - "modeling and performance analysis of clustered device to device networks"
    - "hethetnets heterogeneous traffic distribution in heterogeneous wireless cellular networks"
    - "characterizing spatial patterns of base stations in cellular networks"

Connected through hyperedge HE-3 (induced by source paper "offloading traffic hotspots using moving small cells"):
  with members:
    - "analytical tractability of hexagonal network model with random user location"
    - "performance analysis of small cells deployment under imperfect traffic hotspot localization"
    - "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-4 (induced by source paper "analytical tractability of hexagonal network model with random user location"):
  with members:
    - "asymptotic deployment gain a simple approach to characterize the sinr distribution in general cellular networks"
    - "the mean interference to signal ratio and its key role in cellular and amorphous networks"
    - "the ginibre point process as a model for wireless networks with repulsion"
    - "traffic hotspot localization in 3g and 4g wireless networks using omc metrics"
    - "a tractable approach to coverage and rate in cellular 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)