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: "non coherent capacity and reliability of sparse multipath channels in the wideband regime"
  Abstract: In contrast to the prevalent assumption of rich multipath in information theoretic analysis of wireless channels, physical channels exhibit sparse multipath, especially at large bandwidths. We propose a model for sparse multipath fading channels and present results on the impact of sparsity on non-coherent capacity and reliability in the wideband regime. A key implication of sparsity is that the statistically independent degrees of freedom in the channel, that represent the delay-Doppler diversity afforded by multipath, scale at a sub-linear rate with the signal space dimension (time-bandwidth product). Our analysis is based on a training-based communication scheme that uses short-time Fourier (STF) signaling waveforms. Sparsity in delay-Doppler manifests itself as time-frequency coherence in the STF domain. From a capacity perspective, sparse channels are asymptotically coherent: the gap between coherent and non-coherent extremes vanishes in the limit of large signal space dimension without the need for peaky signaling. From a reliability viewpoint, there is a fundamental tradeoff between channel diversity and learnability that can be optimized to maximize the error exponent at any rate by appropriately choosing the signaling duration as a function of bandwidth.

Connected through hyperedge HE-1 (induced by source paper "optimal constellations for the low snr noncoherent mimo block rayleigh fading channel"):
  with members:
    - "low snr capacity of fading channels mimo and delay spread"
    - "capacity of sparse multipath channels in the ultra wideband regime"
    - "low snr capacity of fading channels with peak and average power constraints"
    - "the noncoherent rician fading channel part i structure of the capacity achieving input"
    - "noncoherent rician fading channel part ii spectral efficiency in the low power regime"
    - "capacity per unit energy of fading channels with a peak constraint"

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)