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 "unified analysis of hetnets using poisson cluster process under max power association"):
  Abstract: Owing to its flexibility in modeling real-world spatial configurations of users and base stations (BSs), the Poisson cluster process (PCP) has recently emerged as an appealing way to model and analyze heterogeneous cellular networks (HetNets). Despite its undisputed relevance to HetNets -- corroborated by the models used in industry -- the PCP's use in performance analysis has been limited. This is primarily because of the lack of analytical tools to characterize performance metrics such as the coverage probability of a user connected to the strongest BS. In this paper, we develop an analytical framework for the evaluation of the coverage probability, or equivalently the complementary cumulative density function (CCDF) of signal-to-interference-and-noise-ratio (SINR), of a typical user in a K-tier HetNet under a max power-based association strategy, where the BS locations of each tier follow either a Poisson point process (PPP) or a PCP. The key enabling step involves conditioning on the parent PPPs of all the PCPs which allows us to express the coverage probability as a product of sum-product and probability generating functionals (PGFLs) of the parent PPPs. In addition to several useful insights, our analysis provides a rigorous way to study the impact of the cluster size on the SINR distribution, which was not possible using existing PPP-based models.

Includes members:
  Member "equi coverage contours in cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "coverage analysis of integrated sub 6ghz mmwave cellular networks with hotspots")
  Member "downlink coverage probability in cellular networks with poisson poisson cluster deployed base stations":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "coverage analysis of integrated sub 6ghz mmwave cellular networks with hotspots")
  Member "3gpp inspired hetnet model using poisson cluster process sum product functionals and downlink coverage":
    also connected through other hyperedges:
      - Hyperedge HE-3 (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-4 (induced by source paper "area spectral efficiency and sinr scaling laws in multi antenna cellular networks")
  Member "stochastic geometry modeling and analysis of single and multi cluster wireless networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "stochastic design and analysis of wireless cloud caching networks")
  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 "interference functionals in poisson networks":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "interference prediction in wireless networks stochastic geometry meets recursive filtering")

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)