human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "the alpha kappa mu shadowed fading distribution statistical characterization and applications"
  Abstract: We introduce the {\alpha}-{\kappa}-{\mu} shadowed ({\alpha}-KMS) fading distribution as a natural generalization of the versatile {\alpha}-{\kappa}-{\mu} and {\alpha}-{\eta}-{\mu} distributions. The {\alpha}-KMS fading distribution unifies a wide set of fading distributions, as it includes the {\alpha}-{\kappa}-{\mu}, {\alpha}- {\eta}-{\mu}, {\alpha}-{\mu}, Weibull, {\kappa}-{\mu} shadowed, Rician shadowed, {\kappa}-{\mu} and {\eta}- {\mu} distributions as special cases, together with classical models like Rice, Nakagami-m, Hoyt, Rayleigh and one-sided Gaussian. Notably, the {\alpha}-KMS distribution reduces to a finite mixture of {\alpha}-{\mu} distributions when the fading parameters {\mu} and m take positive integer values, so that performance analysis over {\alpha}-KMS fading channels can be tackled by leveraging previous (existing) results in the literature for the simpler {\alpha}-{\mu} case. As application examples, important performance metrics like the outage probability and average channel capacity are analyzed.

Connected through hyperedge HE-1 (induced by source paper "on the distribution of the ratio of products of fisher snedecor mathcal f random variables and its applications"):
  with members:
    - "multiple antenna technologies for beyond 5g"
    - "mixed adc dac multipair massive mimo relaying systems performance analysis and power optimization"
    - "on the multivariate gamma gamma distribution with arbitrary correlation and applications in wireless communications"
    - "approximation to distribution of product of random variables using orthogonal polynomials for lognormal density"

Question: Please tell me which class the center node 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)