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: "generalized i mmse for k user gaussian channels"
  Abstract: In this paper, we generalize the fundamental relation between the mutual information and the minimum mean squared error (MMSE) by Guo, Shamai, and Verdu [1] to K-User Gaussian channels. We prove that the derivative of the multiuser mutual information with respect to the signal to noise ratio (SNR) is equal to the total MMSE plus a covariance term with respect to the cross correlation of the multiuser input estimates, the channels and the precoding matrices. We shed light that such relation is a generalized I-MMSE with one step lookahead and lookback, applied to the Successive Interference Cancellation (SIC) in the decoding process.

Connected through hyperedge HE-1 (induced by source paper "a generalized expression for the gradient of mutual information with the application in multiple access channels"):
  with members:
    - "sum rate capacity for symmetric gaussian multiple access channels with feedback"
    - "transmitter optimization in slow fading miso wiretap channel"
    - "pointwise relations between information and estimation in gaussian noise"
    - "mutual information relative entropy and estimation in the poisson channel"
    - "mutual information and minimum mean square error in gaussian channels"

Connected through hyperedge HE-2 (induced by source paper "piggybacking codes for network coding the high low snr regime"):
  with members:
    - "multiuser i mmse"
    - "wireless network information flow a deterministic approach"
    - "an alternative proof for the capacity region of the degraded gaussian mimo broadcast channel"
    - "pipelined encoding for deterministic and noisy 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)