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 continuous time white phase noise channels"):
  Abstract: A continuous-time model for the additive white Gaussian noise (AWGN) channel in the presence of white (memoryless) phase noise is proposed and discussed. It is shown that for linear modulation the output of the baud-sampled filter matched to the shaping waveform represents a sufficient statistic. The analysis shows that the phase noise channel has the same information rate as an AWGN channel but with a penalty on the average signal-to-noise ratio, the amount of penalty depending on the phase noise statistic.

Includes members:
  Member "phase modulation for discrete time wiener phase noise channels with oversampling at high snr":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "models and information rates for wiener phase noise channels")
  Member "multi sample receivers increase information rates for wiener phase noise channels":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "models and information rates for wiener phase noise channels")
  Member "tight upper and lower bounds to the information rate of the phase noise channel":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "lower bound on the capacity of continuous time wiener phase noise channels")
  Member "on wiener phase noise channels at high signal to noise ratio":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "models and information rates for wiener phase noise channels")
  Member "calculation of mutual information for partially coherent gaussian channels with applications to fiber optics":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "models and information rates for wiener phase noise 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)