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: "capacity pre log of noncoherent simo channels via hironaka s theorem"
  Abstract: We find the capacity pre-log of a temporally correlated Rayleigh block-fading SIMO channel in the noncoherent setting. It is well known that for block-length L and rank of the channel covariance matrix equal to Q, the capacity pre-log in the SISO case is given by 1-Q/L. Here, Q/L can be interpreted as the pre-log penalty incurred by channel uncertainty. Our main result reveals that, by adding only one receive antenna, this penalty can be reduced to 1/L and can, hence, be made to vanish in the large-L limit, even if Q/L remains constant as L goes to infinity. Intuitively, even though the SISO channels between the transmit antenna and the two receive antennas are statistically independent, the transmit signal induces enough statistical dependence between the corresponding receive signals for the second receive antenna to be able to resolve the uncertainty associated with the first receive antenna's channel and thereby make the overall system appear coherent. The proof of our main theorem is based on a deep result from algebraic geometry known as Hironaka's Theorem on the Resolution of Singularities.

Connected through hyperedge HE-1 (induced by source paper "generalized degrees freedom of noncoherent mimo with asymmetric links"):
  with members:
    - "enhancing multiuser mimo through opportunistic d2d cooperation"
    - "degrees of freedom of generic block fading mimo channels without a priori channel state information"
    - "gaussian half duplex relay networks improved constant gap and connections with the assignment problem"
    - "on the capacity of large mimo block fading channels"
    - "on noncoherent fading relay channels at high signal to noise ratio"
    - "generalized degrees of freedom of the symmetric gaussian k user interference channel"
    - "gaussian interference channel capacity to within one bit"

Connected through hyperedge HE-2 (induced by source paper "self calibration and bilinear inverse problems via linear least squares"):
  with members:
    - "a non convex blind calibration method for randomised sensing strategies"
    - "empirical chaos processes and blind deconvolution"
    - "rapid robust and reliable blind deconvolution via nonconvex optimization"
    - "through the haze a non convex approach to blind gain calibration for linear random sensing models"
    - "leveraging diversity and sparsity in blind deconvolution"
    - "optimal sample complexity for blind gain and phase calibration"
    - "a greedy blind calibration method for compressed sensing with unknown sensor gains"
    - "an overview of low rank matrix recovery from incomplete observations"

Connected through hyperedge HE-3 (induced by source paper "degrees of freedom of generic block fading mimo channels without a priori channel state information"):
  with members:
    - "generic correlation increases noncoherent mimo capacity"
    - "scaling up mimo opportunities and challenges with very large arrays"
    - "a lower bound on the noncoherent capacity pre log for the mimo channel with temporally correlated fading"
    - "on the capacity of large mimo block fading channels"
    - "noncoherent simo pre log via resolution of singularities"
    - "high snr capacity of wireless communication channels in the noncoherent setting a primer"
    - "on the sensitivity of continuous time noncoherent fading channel capacity"
    - "the simo pre log can be larger than the siso pre log"

Connected through hyperedge HE-4 (induced by source paper "oversampling increases the pre log of noncoherent rayleigh fading channels"):
  with members:
    - "degrees of freedom of generic block fading mimo channels without a priori channel state information"
    - "on wiener phase noise channels at high signal to noise ratio"
    - "on the capacity of large mimo block fading channels"
    - "high snr capacity of wireless communication channels in the noncoherent setting a primer"
    - "on the sensitivity of continuous time noncoherent fading channel capacity"
    - "increased capacity per unit cost by oversampling"

Connected through hyperedge HE-5 (induced by source paper "achievability of nonlinear degrees of freedom in correlatively changing fading channels"):
  with members:
    - "noncoherent simo pre log via resolution of singularities"

Connected through hyperedge HE-6 (induced by source paper "generic correlation increases noncoherent mimo capacity"):
  with members:
    - "a lower bound on the noncoherent capacity pre log for the mimo channel with temporally correlated fading"
    - "joint spatial division and multiplexing"
    - "on the capacity of large mimo block fading channels"

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)