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 achievable rates for long haul fiber optic communications"
  Abstract: Lower bounds on mutual information (MI) of long-haul optical fiber systems for hard-decision and soft-decision decoding are studied. Ready-to-use expressions to calculate the MI are presented. Extensive numerical simulations are used to quantify how changes in the optical transmitter, receiver, and channel affect the achievable transmission rates of the system. Special emphasis is put to the use of different quadrature amplitude modulation formats, channel spacings, digital back-propagation schemes and probabilistic shaping. The advantages of using MI over the prevailing Q-factor as a figure of merit of coded optical systems are also highlighted.

Connected through hyperedge HE-1 (induced by source paper "nonlinearity mitigation in wdm systems models strategies and achievable rates"):
  with members:
    - "improved lower bounds on mutual information accounting for nonlinear signal noise interaction"
    - "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"
    - "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 "improved lower bounds on mutual information accounting for nonlinear signal noise interaction"):
  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"
    - "stochastic digital backpropagation with residual memory compensation"
    - "upper bound on the capacity of a cascade of nonlinear and noisy channels"
    - "capacity of a nonlinear optical channel with finite memory"
    - "optimization of information rate upper and lower bounds for channels with memory"

Connected through hyperedge HE-3 (induced by source paper "achievable information rates for nonlinear fiber communication via end to end autoencoder learning"):
  with members:
    - "end to end deep learning of optical fiber communications"
    - "an introduction to deep learning for the physical layer"
    - "nonlinear interference mitigation via deep neural networks"
    - "design of apsk constellations for coherent optical channels with nonlinear phase noise"
    - "on the per sample capacity of nondispersive optical fibers"

Connected through hyperedge HE-4 (induced by source paper "performance prediction of nonbinary forward error correction in optical transmission experiments"):
  with members:
    - "information rates of next generation long haul optical fiber systems using coded modulation"
    - "sensitivity gains by mismatched probabilistic shaping for optical communication systems"
    - "advances in detection and error correction for coherent optical communications regular irregular and spatially coupled ldpc code designs"
    - "impact of 4d channel distribution on the achievable rates in coherent optical communication experiments"
    - "four dimensional coded modulation with bit wise decoders for future optical communications"
    - "capacity of a nonlinear optical channel with finite memory"
    - "spatially coupled ensembles universally achieve capacity under belief propagation"
    - "channel polarization a method for constructing capacity achieving codes for symmetric binary input memoryless channels"

Connected through hyperedge HE-5 (induced by source paper "information rates of next generation long haul optical fiber systems using coded modulation"):
  with members:
    - "sensitivity gains by mismatched probabilistic shaping for optical communication systems"
    - "impact of 4d channel distribution on the achievable rates in coherent optical communication experiments"
    - "upper bound on the capacity of a cascade of nonlinear and noisy channels"
    - "replacing the soft fec limit paradigm in the design of optical communication systems"
    - "four dimensional coded modulation with bit wise decoders for future optical communications"
    - "capacity of a nonlinear optical channel with finite memory"
    - "staircase codes fec for 100 gb s otn"

Connected through hyperedge HE-6 (induced by source paper "achievable information rates for coded modulation with hard decision decoding for coherent fiber optic systems"):
  with members:
    - "performance prediction of nonbinary forward error correction in optical transmission experiments"
    - "information rates of next generation long haul optical fiber systems using coded modulation"
    - "density evolution for deterministic generalized product codes with higher order modulation"
    - "terminated and tailbiting spatially coupled codes with optimized bit mappings for spectrally efficient fiber optical systems"
    - "staircase codes fec for 100 gb s otn"
    - "approaching capacity at high rates with iterative hard decision decoding"

Connected through hyperedge HE-7 (induced by source paper "on probabilistic shaping of quadrature amplitude modulation for the nonlinear fiber channel"):
  with members:
    - "sensitivity gains by mismatched probabilistic shaping for optical communication systems"
    - "impact of 4d channel distribution on the achievable rates in coherent optical communication experiments"
    - "constellation shaping for wdm systems using 256qam 1024qam with probabilistic optimization"
    - "experimental demonstration of capacity increase and rate adaptation by probabilistically shaped 64 qam"
    - "constant composition distribution matching"
    - "ldpc coded modulation with probabilistic shaping for optical fiber systems"
    - "four dimensional coded modulation with bit wise decoders for future optical communications"
    - "achievable rates for shaped bit metric decoding"

Connected through hyperedge HE-8 (induced by source paper "sensitivity gains by mismatched probabilistic shaping for optical communication systems"):
  with members:
    - "experimental demonstration of capacity increase and rate adaptation by probabilistically shaped 64 qam"
    - "constant composition distribution matching"
    - "ldpc coded modulation with probabilistic shaping for optical fiber systems"
    - "achievable rates for shaped bit metric decoding"
    - "a pragmatic coded modulation scheme for high spectral efficiency fiber optic communications"

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)