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: "asymptotic maximal order statistic for sir in κ μ shadowed fading"
  Abstract: Using tools from extreme value theory (EVT), it is proved that the limiting distribution of the maximum of L independent and identically distributed (i.i.d.) signal-to-interference ratio (SIR) random variables (RVs) is a Frechet distribution, when the user and the interferer signals undergo independent and non-identically distributed (i.n.i.d.) $\kappa-\mu$ shadowed fading. This limiting distribution is used to analyze the outage probability for selection combining (SC). Further, the moments of the maximum is shown to converge to the moments of the Frechet RV. This is used in deriving results for the asymptotic rate for SC. Finally, the rate of convergence of the actual maximum distribution to the Frechet distribution is derived and is analyzed for different $\kappa$ and $\mu$ parameters. Further, results from stochastic ordering are used to analyze the variations in the limiting distribution with respect to variations in the source fading parameters. A close match is observed between Monte-Carlo simulations and the limiting distributions for outage probability and rate.

Connected through hyperedge HE-1 (induced by source paper "transmit power policy and ergodic multicast rate analysis of cognitive radio networks in generalized fading"):
  with members:
    - "asymptotic performance analysis of generalized user selection for interference limited multiuser secondary networks"
    - "mimo underlay cognitive radio optimized power allocation effective number of transmit antennas and harvest transmit tradeoff"
    - "error vector magnitude analysis in generalized fading with co channel interference"
    - "outage probability and rate for kappa mu shadowed fading in interference limited scenario"
    - "coverage analysis in downlink poisson cellular network with kappa mu shadowed fading"
    - "relay selection improves the security reliability trade off in cognitive radio systems"
    - "spectrum sharing multi hop cooperative relaying performance analysis using extreme value theory"
    - "the effects of limited channel knowledge on cognitive radio system capacity"

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)