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: "improved lower bounds on mutual information accounting for nonlinear signal noise interaction"
  Abstract: In fiber-optic communications, evaluation of mutual information (MI) is still an open issue due to the unavailability of an exact and mathematically tractable channel model. Traditionally, lower bounds on MI are computed by approximating the (original) channel with an auxiliary forward channel. In this paper, lower bounds are computed using an auxiliary backward channel, which has not been previously considered in the context of fiber-optic communications. Distributions obtained through two variations of the stochastic digital backpropagation (SDBP) algorithm are used as auxiliary backward channels and these bounds are compared with bounds obtained through the conventional digital backpropagation. Through simulations, higher information rates were achieved with the SDBP, which can be explained by the ability of SDBP to account for nonlinear signal–noise interactions.

Connected through hyperedge HE-1 (induced by source paper "nonlinearity mitigation in wdm systems models strategies and achievable rates"):
  with members:
    - "information rates of next generation long haul optical fiber systems using coded modulation"
    - "impact of 4d channel distribution on the achievable rates in coherent optical communication experiments"
    - "on probabilistic shaping of quadrature amplitude modulation for the nonlinear fiber channel"
    - "upper bound on the capacity of a cascade of nonlinear and noisy channels"
    - "on achievable rates for long haul fiber optic communications"
    - "influence of behavioral models on multiuser channel capacity"
    - "on the per sample capacity of nondispersive optical fibers"

Connected through hyperedge HE-2 (induced by source paper "how to increase the achievable information rate by per channel dispersion compensation"):
  with members:
    - "demodulation and detection schemes for a memoryless optical wdm channel"
    - "impact of 4d channel distribution on the achievable rates in coherent optical communication experiments"

Connected through hyperedge HE-3 (induced by source paper "non parametric estimation of mutual information with application to nonlinear optical fibers"):
  with members:
    - "a non parametric k nearest neighbour entropy estimator"
    - "upper bound on the capacity of a cascade of nonlinear and noisy channels"
    - "capacity of a nonlinear optical channel with finite memory"
    - "mutual information as a figure of merit for optical fiber systems"

Connected through hyperedge HE-4 (induced by source paper "rates achievable on a fiber optical split step fourier channel"):
  with members:
    - "conditions for a monotonic channel capacity"
    - "upper bound on the capacity of a cascade of nonlinear and noisy channels"
    - "upper bound on the capacity of the nonlinear schr odinger 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)