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: "the noncoherent rician fading channel part i structure of the capacity achieving input"
  Abstract: Transmission of information over a discrete-time memoryless Rician fading channel is considered, where neither the receiver nor the transmitter knows the fading coefficients. First, the structure of the capacity-achieving input signals is investigated when the input is constrained to have limited peakedness by imposing either a fourth moment or a peak constraint. When the input is subject to second and fourth moment limitations, it is shown that the capacity-achieving input amplitude distribution is discrete with a finite number of mass points in the low-power regime. A similar discrete structure for the optimal amplitude is proven over the entire signal-to-noise ratio (SNR) range when there is only a peak-power constraint. The Rician fading with the phase-noise channel model, where there is phase uncertainty in the specular component, is analyzed. For this model, it is shown that, with only an average power constraint, the capacity-achieving input amplitude is discrete with a finite number of levels. For the classical average-power-limited Rician fading channel, it is proven that the optimal input amplitude distribution has bounded support.

Connected through hyperedge HE-1 (induced by source paper "a simple capacity lower bound for communication with superimposed pilots"):
  with members:
    - "superimposed pilots are superior for mitigating pilot contamination in massive mimo"
    - "a rate splitting approach to fading channels with imperfect channel state information"
    - "nearest neighbour decoding and pilot aided channel estimation in stationary gaussian flat fading channels"
    - "what is the value of joint processing of pilots and data in block fading channels"

Connected through hyperedge HE-2 (induced by source paper "capacity achieving input distributions in nondispersive optical fibers"):
  with members:
    - "on properties of the support of capacity achieving distributions for additive noise channel models with input cost constraints"
    - "on the finiteness of the capacity of continuous channels"
    - "the asymptotic capacity of the optical fiber"
    - "upper bound on the capacity of a cascade of nonlinear and noisy channels"
    - "information theoretic proofs of entropy power inequalities"

Connected through hyperedge HE-3 (induced by source paper "achievable rates of multidimensional rotationally invariant distributions"):
  with members:
    - "four dimensional coded modulation with bit wise decoders for future optical communications"
    - "interference focusing for simplified optical fiber models with dispersion"
    - "on the per sample capacity of nondispersive optical fibers"

Connected through hyperedge HE-4 (induced by source paper "conditions for a monotonic channel capacity"):
  with members:
    - "capacity of a nonlinear optical channel with finite memory"
    - "calculation of mutual information for partially coherent gaussian channels with applications to fiber optics"
    - "optimal alphabets and binary labelings for bicm at low snr"
    - "lecture notes on network information theory"

Connected through hyperedge HE-5 (induced by source paper "on the capacity of vector gaussian channels with bounded inputs"):
  with members:
    - "on the boundedness of the support of optimal input measures for rayleigh fading channels"

Connected through hyperedge HE-6 (induced by source paper "capacity of gaussian channels with duty cycle and power constraints"):
  with members:
    - "bits through deterministic relay cascades with half duplex constraint"
    - "virtual full duplex wireless communication via rapid on off division duplex"
    - "capacity for half duplex line networks with two sources"
    - "virtual full duplex wireless broadcasting via compressed sensing"

Connected through hyperedge HE-7 (induced by source paper "energy efficient full diversity collaborative unitary space time block code design via unique factorization of signals"):
  with members:
    - "full diversity codes for miso systems equipped with linear or ml detectors"
    - "four group decodable space time block codes"
    - "on full diversity space time block codes with partial interference cancellation group decoding"
    - "on fast decodable space time block codes"
    - "quasi orthogonal stbc with minimum decoding complexity"
    - "noncoherent rician fading channel part ii spectral efficiency in the low power regime"

Connected through hyperedge HE-8 (induced by source paper "awgn channel under time varying amplitude constraints with causal information at the transmitter"):
  with members:
    - "information theoretic analysis of an energy harvesting communication system"

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)