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: "outage probability and rate for kappa mu shadowed fading in interference limited scenario"
  Abstract: The $\kappa$-$\mu$ shadowed fading model is a very general fading model as it includes both $\kappa$-$\mu$ and $\eta$-$\mu$ as special cases. In this work, we derive the expression for outage probability when the signal-of-interest (SoI) and interferers both experience $\kappa$-$\mu$ shadowed fading in an interference limited scenario. The derived expression is valid for arbitrary SoI parameters, arbitrary $\kappa$ and $\mu$ parameters for all interferers and any value of the parameter $m$ for the interferers excepting the limiting value of $m\rightarrow \infty$. The expression can be expressed in terms of Pochhammer integral where the integrands of integral only contains elementary functions. The outage probability expression is then simplified for various special cases, especially when SoI experiences $\eta$-$\mu$ or $\kappa$-$\mu$ fading. Further, the rate expression is derived when the SoI experiences $\kappa$-$\mu$ shadowed fading with integer values of $\mu$, and interferers experience $\kappa$-$\mu$ shadowed fading with arbitrary parameters. The rate expression can be expressed in terms of sum of Lauricella's function of the fourth kind. The utility of our results is demonstrated by using the derived expression to study and compare FFR and SFR in the presence of $\kappa$-$\mu$ shadowed fading. Extensive simulation results are provided and these further validate our theoretical results.

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"
    - "asymptotic maximal order statistic for sir in κ μ shadowed fading"
    - "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"
    - "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"

Connected through hyperedge HE-2 (induced by source paper "asymptotic maximal order statistic for sir in κ μ shadowed fading"):
  with members:
    - "error vector magnitude analysis in generalized fading with co channel interference"
    - "coverage analysis in downlink poisson cellular network with kappa mu shadowed fading"
    - "massive mimo ten myths and one critical question"
    - "uplink achievable rate for massive mimo systems with low resolution adc"
    - "massive mimo performance evaluation based on measured propagation data"
    - "massive mimo for next generation wireless systems"
    - "on the sum of correlated squared kappa mu shadowed random variables and its application to performance analysis of mrc"
    - "spectrum sharing multi hop cooperative relaying performance analysis using extreme value theory"

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)