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 "interference modeling for cellular networks under beamforming transmission"):
  Abstract: We propose analytical models for the interference power distribution in a cellular system employing MIMO beamforming in rich and limited scattering environments, which capture non line-of-sight signal propagation in the microwave and mm-wave bands, respectively. Two candidate models are considered: the inverse Gaussian and the inverse Weibull, both are two-parameter heavy tail distributions. We further propose a mixture of these two distributions as a model with three parameters. To estimate the parameters of these distributions, three approaches are used: moment matching, individual distribution maximum likelihood estimation (MLE), and mixture distribution MLE with a designed expectation maximization algorithm. We then introduce simple fitted functions for the mixture model parameters as polynomials of the channel path loss exponent and shadowing variance. To measure the goodness of these models, the information-theoretic metric relative entropy is used to capture the distance from the model distribution to a reference one. The interference models are tested against data obtained by simulating a cellular network based on stochastic geometry. The results show that the three-parameter mixture model offers remarkably good fit to simulated interference power. The mixture model is further used to analyze the capacity of a cellular network employing joint transmit and receive beamforming and confirms a good fit with simulation.

Includes members:
  Member "understanding noise and interference regimes in 5g millimeter wave cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "joint path selection and rate allocation framework for 5g self backhauled mm wave networks")
  Member "gaussian approximation for the downlink interference in heterogeneous cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "energy efficient power and channel allocation in underlay device to multi device communications")
  Member "coverage in heterogeneous downlink millimeter wave cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "millimeter wave integrated access and backhaul in 5g performance analysis and design insights")
  Member "a stochastic geometry framework for analyzing pairwise cooperative cellular networks":
    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 "a survey of millimeter wave mmwave communications for 5g opportunities and challenges":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "a distributed multi rf chain hybrid mmwave scheme for small cell systems")
  Member "probabilistic omnidirectional path loss models for millimeter wave outdoor communications":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "early acceptance matching game for user association in 5g cellular hetnet")
  Member "analysis of a cooperative strategy for a large decentralized wireless network":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "performance evaluation of advanced relaying protocols in large wireless networks")
  Member "coverage and rate analysis for millimeter wave cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "optimizing information freshness in wireless networks a stochastic geometry approach")

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)