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: "analog network coding in general snr regime performance of a greedy scheme"
  Abstract: The problem of maximum rate achievable with analog network coding for a unicast communication over a layered relay network with directed links is considered. A relay node performing analog network coding scales and forwards the signals received at its input. Recently this problem has been considered under certain assumptions on per node scaling factor and received SNR. Previously, we established a result that allows us to characterize the optimal performance of analog network coding in network scenarios beyond those that can be analyzed using the approaches based on such assumptions. #R##N#The key contribution of this work is a scheme to greedily compute a lower bound to the optimal rate achievable with analog network coding in the general layered networks. This scheme allows for exact computation of the optimal achievable rates in a wider class of layered networks than those that can be addressed using existing approaches. For the specific case of Gaussian N-relay diamond network, to the best of our knowledge, the proposed scheme provides the first exact characterization of the optimal rate achievable with analog network coding. Further, for general layered networks, our scheme allows us to compute optimal rates within a constant gap from the cut-set upper bound asymptotically in the source power.

Connected through hyperedge HE-1 (induced by source paper "analog network coding in nonlinear chains"):
  with members:
    - "analog network coding in general snr regime"
    - "analog network coding in the generalized high snr regime"
    - "amplify and forward in wireless relay networks"
    - "network beamforming using relays with perfect channel information"
    - "optimal relay functionality for snr maximization in memoryless relay networks"

Connected through hyperedge HE-2 (induced by source paper "optimal amplify and forward schemes for relay channels with correlated relay noise"):
  with members:
    - "analog network coding in general snr regime"
    - "on design of collaborative beamforming for two way relay networks"
    - "network beamforming using relays with perfect channel information"
    - "optimal beamforming for two way multi antenna relay channel with analogue network coding"

Connected through hyperedge HE-3 (induced by source paper "analog network coding in general snr regime performance of network simplification"):
  with members:
    - "analog network coding in general snr regime"
    - "the approximate capacity of the gaussian n relay diamond network"
    - "analog network coding in the generalized high snr regime"
    - "amplify and forward in wireless relay networks"
    - "wireless network simplification the gaussian n relay diamond network"
    - "a simple cooperative diversity method based on network path selection"
    - "optimal relay functionality for snr maximization in memoryless relay networks"

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)