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 "on physical layer security over fox s h function wiretap fading channels"):
  Abstract: Most of the well-known fading distributions, if not all of them, could be encompassed by the Fox's   $H$  -function fading. Consequently, we investigate the physical layer security over Fox's   $H$  -function fading wiretap channels, in the presence of non-colluding and colluding eavesdroppers. In particular, for the non-colluding scenario, closed-form expressions are derived for the secrecy outage probability (SOP), the probability of non-zero secrecy capacity, and the average secrecy capacity. These expressions are given in terms of either univariate or bivariate Fox's   $H$  -function. In order to show the effectiveness of our derivations, three metrics are respectively listed over the following frequently used fading channels, including Rayleigh, Weibull, Nakagami-  $m$  ,   $\alpha -\mu$  , Fisher-Snedecor (F-S)   $\mathcal {F}$  , and extended generalized-  $\mathcal {K}$  . Our tractable results are not only straightforward and general, but also feasible and applicable, especially the SOP, which is usually limited to the lower bound in the literature due to the difficulty of deriving closed-from analytical expressions. For the colluding scenario, a super eavesdropper equipped with maximal ratio combining (MRC) or selection-combining (SC) schemes is characterized. The lower bound of SOP and exact PNZ are thereafter derived with closed-form expressions in terms of the multivariate Fox's   $H$  -function. In order to validate the accuracy of our analytical results, Monte Carlo simulations are subsequently conducted for the aforementioned fading channels. One can observe that for the former non-colluding scenario, we have perfect agreement between the exact analytical and simulation results, and highly accurate approximations between the exact and asymptotic analytical results. On the contrary, the SOP and PNZ of colluding eavesdropper is greatly degraded with the increase of the number of eavesdroppers. Also, the so-called super eavesdropper with MRC is much powerful to wiretap the main channel than the one with SC.

Includes members:
  Member "rician k factor based analysis of xlos service probability in 5g outdoor ultra dense networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "distribution of the sum of fisher snedecor mathcal f random variables and its applications")
  Member "performance analysis of project and forward relaying in mixed mimo pinhole and rayleigh dual hop channel":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "fundamental limits of spectrum sharing for noma based cooperative relaying under a peak interference constraint")
  Member "secrecy capacity analysis over kappa mu fading channels theory and applications":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "performance analysis of physical layer security over fluctuating beckmann fading channels")
  Member "a novel unified expression for the capacity and bit error probability of wireless communication systems over generalized fading channels":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "hetnets coverage modeling and analysis over fox s mathcal h fading channels")

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)