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: "conditions for a monotonic channel capacity"
  Abstract: Motivated by results in optical communications, where the performance can degrade dramatically if the transmit power is sufficiently increased, the channel capacity is characterized for various kinds of memoryless vector channels. It is proved that for all static point-to-point channels, the channel capacity under an equal-power constraint is a nondecreasing function of power. As a consequence, maximizing the mutual information over all input distributions with a certain power is for such channels equivalent to maximizing it over the larger set of input distributions with upperbounded power. The channel coding theorem is formally proved for an equal-power constraint. For interference channels such as optical wavelength-division multiplexing systems, the primary channel capacity is always nondecreasing with power if all interferers transmit with identical distributions as the primary user. Also, if all input distributions in an interference channel are optimized jointly, then the achievable sum-rate capacity is again nondecreasing. The results generalize to the channel capacity as a function of a wide class of costs, not only power.

Connected through hyperedge HE-1 (induced by source paper "linear and nonlinear frequency division multiplexing"):
  with members:
    - "a novel detection strategy for nonlinear frequency division multiplexing"
    - "decision feedback detection strategy for nonlinear frequency division multiplexing"
    - "communication using eigenvalues of higher multiplicity of the nonlinear fourier transform"
    - "the kolmogorov zakharov model for optical fiber communication"
    - "correlated eigenvalues optical communications"
    - "why noise and dispersion may seriously hamper nonlinear frequency division multiplexing"
    - "polarization division multiplexing based on the nonlinear fourier transform"
    - "nonlinear frequency division multiplexing in the focusing regime"

Connected through hyperedge HE-2 (induced by source paper "the asymptotic capacity of the optical fiber"):
  with members:
    - "nonlinear frequency division multiplexing"
    - "models and information rates for multiuser optical fiber channels with nonlinearity and dispersion"
    - "upper bound on the capacity of a cascade of nonlinear and noisy channels"
    - "upper bound on the capacity of the nonlinear schr odinger channel"
    - "information transmission using the nonlinear fourier transform part ii numerical methods"
    - "information transmission using the nonlinear fourier transform part i mathematical tools"
    - "information transmission using the nonlinear fourier transform part iii spectrum modulation"
    - "transmission of information via the non linear scroedinger equation the random gaussian input case"

Connected through hyperedge HE-3 (induced by source paper "on properties of the support of capacity achieving distributions for additive noise channel models with input cost constraints"):
  with members:
    - "on the finiteness of the capacity of continuous channels"
    - "information theoretic proofs of entropy power inequalities"

Connected through hyperedge HE-4 (induced by source paper "rates achievable on a fiber optical split step fourier channel"):
  with members:
    - "improved lower bounds on mutual information accounting for nonlinear signal noise interaction"
    - "upper bound on the capacity of a cascade of nonlinear and noisy channels"
    - "upper bound on the capacity of the nonlinear schr odinger channel"

Connected through hyperedge HE-5 (induced by source paper "influence of behavioral models on multiuser channel capacity"):
  with members:
    - "capacity of a nonlinear optical channel with finite memory"

Connected through hyperedge HE-6 (induced by source paper "optimal input signal distribution and per sample mutual information for nondispersive nonlinear optical fiber channel in large snr limit"):
  with members:
    - "capacity of a nonlinear optical channel with finite memory"

Connected through hyperedge HE-7 (induced by source paper "information transmission using the nonlinear fourier transform part iii spectrum modulation"):
  with members:
    - "information transmission using the nonlinear fourier transform part ii numerical methods"
    - "information transmission using the nonlinear fourier transform part i mathematical tools"
    - "on the achievable communication rates of generalized soliton transmission systems"
    - "on the per sample capacity of nondispersive optical fibers"
    - "channels that heat up"

Connected through hyperedge HE-8 (induced by source paper "capacity of a nonlinear optical channel with finite memory"):
  with members:
    - "calculation of mutual information for partially coherent gaussian channels with applications to fiber optics"
    - "channels that heat up"

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)