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: "tight lower bounds on the contact distance distribution in poisson hole process"
  Abstract: In this letter, we derive new lower bounds on the cumulative distribution function (CDF) of the contact distance in the Poisson Hole Process (PHP) for two cases: (i) reference point is selected uniformly at random from $\mathbb{R}^2$ independently of the PHP, and (ii) reference point is located at the center of a hole selected uniformly at random from the PHP. While one can derive upper bounds on the CDF of contact distance by simply ignoring the effect of holes, deriving lower bounds is known to be relatively more challenging. As a part of our proof, we introduce a tractable way of bounding the effect of all the holes in a PHP, which can be used to study other properties of a PHP as well.

Connected through hyperedge HE-1 (induced by source paper "php based model and analysis of millimeter wave heterogeneous cellular network"):
  with members:
    - "poisson hole process theory and applications to wireless networks"
    - "coverage in heterogeneous downlink millimeter wave cellular networks"
    - "performance impact of los and nlos transmissions in dense cellular networks"
    - "stochastic geometry modeling and analysis of multi tier millimeter wave cellular networks"
    - "d2d enhanced heterogeneous cellular networks with dynamic tdd"
    - "downlink cellular network analysis with multi slope path loss models"
    - "tractable model for rate in self backhauled millimeter wave cellular networks"
    - "coverage and rate analysis for millimeter wave cellular networks"

Connected through hyperedge HE-2 (induced by source paper "coexistence of rf powered iot and a primary wireless network with secrecy guard zones"):
  with members:
    - "power allocation for secure swipt systems with wireless powered cooperative jamming"
    - "secrecy outage analysis for downlink transmissions in the presence of randomly located eavesdroppers"
    - "modeling and analysis of cellular networks using stochastic geometry a tutorial"
    - "stochastic geometry based comparison of secrecy enhancement techniques in d2d networks"
    - "a primer on cellular network analysis using stochastic geometry"
    - "spatio temporal interference correlation and joint coverage in cellular networks"
    - "mimo wiretap channel under receiver side power constraints with applications to wireless power transfer and cognitive radio"
    - "secrecy wireless information and power transfer in fading wiretap channel"

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)