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: "coverage and capacity scaling laws in downlink ultra dense cellular networks"
  Abstract: Driven by new types of wireless devices and the proliferation of bandwidth-intensive applications, data traffic and the corresponding network load are increasing dramatically. Network densification has been recognized as a promising and efficient way to provide higher network capacity and enhanced coverage. Most prior work on performance analysis of ultra-dense networks (UDNs) has focused on random spatial deployment with idealized singular path loss models and Rayleigh fading. In this paper, we consider a more precise and general model, which incorporates multi-slope path loss and general fading distributions. We derive the tail behavior and scaling laws for the coverage probability and the capacity considering strongest base station association in a Poisson field network. Our analytical results identify the regimes in which the signal-to-interference-plus-noise ratio (SINR) either asymptotically grows, saturates, or decreases with increasing network density. We establish general results on when UDNs lead to worse or even zero SINR coverage and capacity, and we provide crisp insights on the fundamental limits of wireless network densification.

Connected through hyperedge HE-1 (induced by source paper "downlink cellular network analysis with los nlos propagation and elevated base stations"):
  with members:
    - "sinr and throughput of dense cellular networks with stretched exponential path loss"
    - "modeling and analyzing millimeter wave cellular systems"
    - "performance analysis of ultra dense networks with elevated base stations"
    - "performance limits of network densification"
    - "power beacon assisted millimeter wave ad hoc networks"
    - "a 3 d spatial model for in building wireless networks with correlated shadowing"
    - "study on the idle mode capability with los and nlos transmissions"
    - "impact of los nlos propagation and path loss in ultra dense cellular networks"

Connected through hyperedge HE-2 (induced by source paper "sinr and throughput of dense cellular networks with stretched exponential path loss"):
  with members:
    - "effect of densification on cellular network performance with bounded pathloss model"
    - "modeling and analysis of cellular networks using stochastic geometry a tutorial"
    - "ergodic spectral efficiency in mimo cellular networks"
    - "a primer on cellular network analysis using stochastic geometry"
    - "study on the idle mode capability with los and nlos transmissions"
    - "unified stochastic geometry modeling and analysis of cellular networks in los nlos and shadowed fading"
    - "modeling cellular networks in fading environments with dominant specular components"
    - "the intensity matching approach a tractable stochastic geometry approximation to system level analysis of cellular networks"

Connected through hyperedge HE-3 (induced by source paper "stochastic geometry analysis of ultra dense networks impact of antenna height and performance limits"):
  with members:
    - "the major and minor factors in the performance analysis of ultra dense networks"
    - "on the performance of practical ultra dense networks the major and minor factors"
    - "performance impact of base station antenna heights in dense cellular networks"
    - "please lower small cell antenna heights in 5g"
    - "performance impact of los and nlos transmissions in dense cellular networks"
    - "are we approaching the fundamental limits of wireless network densification"
    - "sinr and throughput scaling in ultradense urban cellular networks"
    - "downlink cellular network analysis with multi slope path loss models"

Connected through hyperedge HE-4 (induced by source paper "performance analysis of ultra dense networks with elevated base stations"):
  with members:
    - "modeling and analyzing millimeter wave cellular systems"
    - "downlink cellular network analysis with los nlos propagation and elevated base stations"
    - "a 3 d spatial model for in building wireless networks with correlated shadowing"
    - "impact of los nlos propagation and path loss in ultra dense cellular networks"
    - "please lower small cell antenna heights in 5g"
    - "performance impact of los and nlos transmissions in dense cellular networks"
    - "are we approaching the fundamental limits of wireless network densification"
    - "downlink cellular network analysis with multi slope path loss models"

Connected through hyperedge HE-5 (induced by source paper "performance limits of network densification"):
  with members:
    - "how dense is ultra dense for wireless networks from far to near field communications"
    - "impact of los nlos propagation and path loss in ultra dense cellular networks"
    - "performance impact of los and nlos transmissions in dense cellular networks"
    - "a unified fading model using infinitely divisible distributions"
    - "towards 1 gbps ue in cellular systems understanding ultra dense small cell deployments"
    - "spectral efficiency scaling laws in dense random wireless networks with multiple receive antennas"
    - "downlink cellular network analysis with multi slope path loss models"
    - "modeling and analysis of k tier downlink heterogeneous 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)