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 "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.

Includes members:
  Member "error vector magnitude analysis in generalized fading with co channel interference":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "transmit power policy and ergodic multicast rate analysis of cognitive radio networks in generalized fading")
  Member "outage probability and rate for kappa mu shadowed fading in interference limited scenario":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "transmit power policy and ergodic multicast rate analysis of cognitive radio networks in generalized fading")
  Member "coverage analysis in downlink poisson cellular network with kappa mu shadowed fading":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "transmit power policy and ergodic multicast rate analysis of cognitive radio networks in generalized fading")
  Member "massive mimo ten myths and one critical question":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "deep learning for massive mimo channel state acquisition and feedback")
  Member "uplink achievable rate for massive mimo systems with low resolution adc":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "asymptotic regime analysis of noma uplink networks under qos delay constraints")
  Member "massive mimo performance evaluation based on measured propagation data":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "massive mimo asymptotics for ray based propagation channels")
  Member "massive mimo for next generation wireless systems":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "joint power control and lsfd for wireless powered cell free massive mimo")
  Member "on the sum of correlated squared kappa mu shadowed random variables and its application to performance analysis of mrc":
    also connected through other hyperedges:
      - Hyperedge HE-8 (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)