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 "information rates of next generation long haul optical fiber systems using coded modulation"):
  Abstract: A comprehensive study of the coded performance of long-haul spectrally-efficient WDM optical fiber transmission systems with different coded modulation decoding structures is presented. Achievable information rates are derived for three different square quadrature-amplitude modulation (QAM) formats and the optimal format is identified as a function of distance and specific decoder implementation. The four cases analyzed combine hard-decision (HD) or soft-decision (SD) decoding together with either a bit-wise or a symbol-wise demapper, the last two suitable for binary and nonbinary codes, respectively. The information rates achievable for each scheme are calculated based on the mismatched decoder principle. These quantities represent true indicators of the coded performance of the system for specific decoder implementations and when the modulation format and its input distribution are fixed. In combination with the structure of the decoder, two different receiver-side equalization strategies are also analyzed: electronic dispersion compensation and digital backpropagation. We show that, somewhat unexpectedly, schemes based on nonbinary HD codes can achieve information rates comparable to SD decoders and that, when SD is used, switching from a symbol-wise to a bit-wise decoder results in a negligible penalty. Conversely, from an information-theoretic standpoint, HD binary decoders are shown to be unsuitable for spectrally-efficient, long-haul systems.

Includes members:
  Member "sensitivity gains by mismatched probabilistic shaping for optical communication systems":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "markov chain monte carlo methods for lattice gaussian sampling convergence analysis and enhancement")
  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 "upper bound on the capacity of a cascade of nonlinear and noisy channels":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "nonlinearity mitigation in wdm systems models strategies and achievable rates")
  Member "replacing the soft fec limit paradigm in the design of optical communication systems":
    also connected through other hyperedges:
      (none)
  Member "on achievable rates for long haul fiber optic communications":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "nonlinearity mitigation in wdm systems models strategies and achievable rates")
  Member "four dimensional coded modulation with bit wise decoders for future optical communications":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "introducing enumerative sphere shaping for optical communication systems with short blocklengths")
  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 "staircase codes fec for 100 gb s otn":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "finite length scaling of spatially coupled ldpc codes under window decoding over the bec")

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)