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: "wireless networks appear poissonian due to strong shadowing"
  Abstract: Geographic locations of cellular base stations sometimes can be well fitted with spatial homogeneous Poisson point processes. In this paper we make a complementary observation: In the presence of the log-normal shadowing of sufficiently high variance, the statistics of the propagation loss of a single user with respect to different network stations are invariant with respect to their geographic positioning, whether regular or not, for a wide class of empirically homogeneous networks. Even in perfectly hexagonal case they appear as though they were realized in a Poisson network model, i.e., form an inhomogeneous Poisson point process on the positive half-line with a power-law density characterized by the path-loss exponent. At the same time, the conditional distances to the corresponding base stations, given their observed propagation losses, become independent and log-normally distributed, which can be seen as a decoupling between the real and model geometry. The result applies also to Suzuki (Rayleigh-log-normal) propagation model. We use Kolmogorov-Smirnov test to empirically study the quality of the Poisson approximation and use it to build a linear-regression method for the statistical estimation of the value of the path-loss exponent.

Connected through hyperedge HE-1 (induced by source paper "wireless network signals with moderately correlated shadowing still appear poisson"):
  with members:
    - "ergodic spectral efficiency in mimo cellular networks"
    - "the intensity matching approach a tractable stochastic geometry approximation to system level analysis of cellular networks"
    - "stronger wireless signals appear more poisson"
    - "studying the sinr process of the typical user in poisson networks by using its factorial moment measures"
    - "average rate of downlink heterogeneous cellular networks over generalized fading channels a stochastic geometry approach"
    - "a tractable approach to coverage and rate in cellular networks"

Connected through hyperedge HE-2 (induced by source paper "performance laws of large heterogeneous cellular networks"):
  with members:
    - "what frequency bandwidth to run cellular network in a given country a downlink dimensioning problem"
    - "how user throughput depends on the traffic demand in large cellular networks"
    - "equivalence and comparison of heterogeneous cellular networks"
    - "analysis of cell load coupling for lte network planning and optimization"
    - "modeling and analysis of k tier downlink heterogeneous cellular networks"
    - "multi tier network performance analysis using a shotgun cellular system"
    - "a tractable approach to coverage and rate in cellular networks"

Connected through hyperedge HE-3 (induced by source paper "studying the sinr process of the typical user in poisson networks by using its factorial moment measures"):
  with members:
    - "a stochastic geometry framework for analyzing pairwise cooperative cellular networks"
    - "the performance of successive interference cancellation in random wireless networks"
    - "successive interference cancellation in heterogeneous cellular networks"
    - "sinr based k coverage probability in cellular networks with arbitrary shadowing"
    - "equivalence and comparison of heterogeneous cellular networks"
    - "heterogeneous cellular networks with flexible cell association a comprehensive downlink sinr analysis"
    - "modeling and analysis of k tier downlink heterogeneous cellular networks"
    - "downlink coverage analysis in a heterogeneous cellular network"

Connected through hyperedge HE-4 (induced by source paper "statistical modeling and probabilistic analysis of cellular networks with determinantal point processes"):
  with members:
    - "studying the sinr process of the typical user in poisson networks by using its factorial moment measures"
    - "the ginibre point process as a model for wireless networks with repulsion"
    - "hetnets and massive mimo modeling potential gains and performance analysis"
    - "downlink mimo hetnets modeling ordering results and performance analysis"
    - "load aware modeling and analysis of heterogeneous cellular networks"
    - "modeling heterogeneous network interference using poisson point processes"
    - "modeling and analysis of k tier downlink heterogeneous cellular networks"
    - "series expansion for interference in wireless 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)