human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "stochastic geometry modeling and analysis of single and multi cluster wireless networks"):
  Abstract: This paper develops a stochastic geometry-based approach for the modeling and analysis of single- and multi-cluster wireless networks. We first define finite homogeneous Poisson point processes to model the number and locations of the transmitters in a confined region as a single-cluster wireless network. We study the coverage probability for a reference receiver for two strategies; closest-selection, where the receiver is served by the closest transmitter among all transmitters, and uniform-selection, where the serving transmitter is selected randomly with uniform distribution. Second, using Matern cluster processes, we extend our model and analysis to multi-cluster wireless networks. Here, the receivers are modeled in two types, namely, closed- and open-access. Closed-access receivers are distributed around the cluster centers of the transmitters according to a symmetric normal distribution and can be served only by the transmitters of their corresponding clusters. Open-access receivers, on the other hand, are placed independently of the transmitters and can be served by all transmitters. In all cases, the link distance distribution and the Laplace transform (LT) of the interference are derived. We also derive closed-form lower bounds on the LT of the interference for single-cluster wireless networks. The impact of different parameters on the performance is also investigated.

Includes members:
  Member "3gpp inspired hetnet model using poisson cluster process sum product functionals and downlink coverage":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "joint energy and sinr coverage in spatially clustered rf powered iot network")
  Member "modeling and analysis of cellular networks using stochastic geometry a tutorial":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "area spectral efficiency and sinr scaling laws in multi antenna cellular networks")
  Member "fundamentals of modeling finite wireless networks using binomial point process":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "air to air communications beyond 5g a novel 3d comp transmission scheme")
  Member "a primer on cellular network analysis using stochastic geometry":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "area spectral efficiency and sinr scaling laws in multi antenna cellular networks")
  Member "optimal geographic caching in finite wireless networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "mitigating interference in content delivery networks by spatial signal alignment the approach of shot noise ratio")
  Member "enriched k tier hetnet model to enable the analysis of user centric small cell deployments":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "joint energy and sinr coverage in spatially clustered rf powered iot network")
  Member "poisson cluster process based analysis of hetnets with correlated user and base station locations":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "joint energy and sinr coverage in spatially clustered rf powered iot network")
  Member "nearest neighbor and contact distance distributions for thomas cluster process":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "on the coverage performance of boolean poisson cluster models for wireless sensor networks")

Question: Please tell me which class the source paper 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.IT(Information Theory)