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: "on stochastic orders and fast fading multiuser channels with statistical csit"
  Abstract: In this paper, we investigate the ergodic capacity of fast fading Gaussian multiuser channels when only the statistics of the channel state are known at the transmitter. In general, the characterization of capacity regions of multiuser channels with only statistical channel state information at the transmitter (CSIT) is open. Instead of directly matching achievable rate regions and the corresponding outer bounds, in this work we resort to classifying the random channels through their probability distributions. To be more precise, in order to attain capacity results, we first derive sufficient conditions to attain some information theoretic channel orders such as degraded and strong/very strong interference by applying the usual stochastic order and exploiting the same marginal property such that the capacity regions of the memoryless Gaussian multiuser channels can be characterized. These include Gaussian interference channels, Gaussian broadcast channels, and Gaussian wiretap channels/secret key generation. We also extend the framework to channels with a specific memory structure, namely, channels with finite-state, wherein the Markov fading channel is discussed as a special case. Several practical examples such as Rayleigh fading and Nakagami-\textit{m} fading, etc., illustrate the application of the derived results.

Connected through hyperedge HE-1 (induced by source paper "reliable communications over dependent fading wireless channels"):
  with members:
    - "a new asymptotic analysis technique for diversity receptions over correlated lognormal fading channels"
    - "what will 5g be"
    - "quasi static multiple antenna fading channels at finite blocklength"

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)