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 "modeling and analysis of wireless channels via the mixture of gaussian distribution"):
  Abstract: In this paper, we consider a unified approach to model wireless channels by the mixture of Gaussian (MoG) distribution. The proposed approach provides an accurate approximation for the envelope and the signal-to-noise ratio (SNR) distributions of wireless fading channels. Simulation results have shown that the proposed model can accurately characterize multipath and composite fading channels. We utilize the well-known expectation–maximization (EM) algorithm to estimate the parameters of the MoG distribution and further utilize the Bayesian information criterion (BIC) to determine the number of mixture components automatically. We employ the Kullback–Leibler (KL) divergence and the mean-square-error (MSE) criteria to demonstrate that the proposed distribution provides both high accuracy and low computational complexity. Additionally, we provide closed-form expressions or approximations for several performance metrics used in wireless communication systems, including the moment generating function (MGF), the raw moments, the amount of fading (AF), the outage probability, the average channel capacity, and the probability of energy detection for cognitive radio (CR). Numerical analysis and Monte Carlo simulation results are presented to corroborate the analytical results.

Includes members:
  Member "the kappa mu shadowed fading model unifying the kappa mu and eta mu distributions":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "on some unifications arising from the mimo rician shadowed model")
  Member "on the capacity of the underwater acoustic channel with dominant noise sources":
    also connected through other hyperedges:
      (none)
  Member "statistical characterization of kappa mu shadowed fading":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "outage probability and rate for kappa mu shadowed fading in interference limited scenario")

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)