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 "enriched k tier hetnet model to enable the analysis of user centric small cell deployments"):
  Abstract: One of the principal underlying assumptions of current approaches to the analysis of heterogeneous cellular networks (HetNets) with random spatial models is the uniform distribution of users independent of the base station (BS) locations. This assumption is not quite accurate, especially for user-centric capacity-driven small cell deployments where low-power BSs are deployed in the areas of high user density, thus inducing a natural correlation in the BS and user locations. In order to capture this correlation, we enrich the existing K-tier Poisson Point Process (PPP) HetNet model by considering user locations as Poisson Cluster Process (PCP) with the BSs at the cluster centers. In particular, we provide the formal analysis of the downlink coverage probability in terms of a general density functions describing the locations of users around the BSs. The derived results are specialized for two cases of interest: (i) Thomas cluster process, where the locations of the users around BSs are Gaussian distributed, and (ii) Mat\'ern cluster process, where the users are uniformly distributed inside a disc of a given radius. Tight closed-form bounds for the coverage probability in these two cases are also derived. Our results demonstrate that the coverage probability decreases as the size of user clusters around BSs increases, ultimately collapsing to the result obtained under the assumption of PPP distribution of users independent of the BS locations when the cluster size goes to infinity. Using these results, we also handle mixed user distributions consisting of two types of users: (i) uniformly distributed, and (ii) clustered around certain tiers.

Includes members:
  Member "modeling and analysis of cellular networks using stochastic geometry a tutorial":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "area spectral efficiency and sinr scaling laws in multi antenna cellular networks")
  Member "a primer on cellular network analysis using stochastic geometry":
    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 cluster centric content placement in cache enabled device to device networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "stochastic design and analysis of wireless cloud caching networks")
  Member "poisson cluster process based analysis of hetnets with correlated user and base station locations":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "joint energy and sinr coverage in spatially clustered rf powered iot network")
  Member "system level analysis of heterogeneous networks under imperfect traffic hotspot localization":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "coverage in downlink heterogeneous mmwave cellular networks with user centric small cell deployment")
  Member "poisson hole process theory and applications to wireless networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "d2d multicast in underlay cellular networks with exclusion zones")
  Member "modeling and performance analysis of clustered device to device networks":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "optimizing joint probabilistic caching and channel access for clustered d2d networks")
  Member "hethetnets heterogeneous traffic distribution in heterogeneous wireless cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "deployment of drone base stations for cellular communication without apriori user distribution information")

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)