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 "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.

Includes members:
  Member "information rates of next generation long haul optical fiber systems using coded modulation":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "nonlinearity mitigation in wdm systems models strategies and achievable rates")
  Member "impact of 4d channel distribution on the achievable rates in coherent optical communication experiments":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "nonlinearity mitigation in wdm systems models strategies and achievable rates")
  Member "stochastic digital backpropagation with residual memory compensation":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "artificial intelligence ai methods in optical networks a comprehensive survey")
  Member "upper bound on the capacity of a cascade of nonlinear and noisy channels":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "nonlinearity mitigation in wdm systems models strategies and achievable rates")
  Member "on achievable rates for long haul fiber optic communications":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "nonlinearity mitigation in wdm systems models strategies and achievable rates")
  Member "capacity of a nonlinear optical channel with finite memory":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "the log log growth of channel capacity for nondispersive nonlinear optical fiber channel in intermediate power range extension of the model")
  Member "optimization of information rate upper and lower bounds for channels with memory":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "bounding and estimating the classical information rate of quantum channels with memory")

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)