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: "on the capacity of multiple access channels with state information and feedback"
  Abstract: In this paper, the multiple access channel (MAC) with channel state is analyzed in a scenario where a) the channel state is known non-causally to the transmitters and b) there is perfect causal feedback from the receiver to the transmitters. An achievable region and an outer bound are found for a discrete memoryless MAC that extend existing results, bringing together ideas from the two separate domains of MAC with state and MAC with feedback. Although this achievable region does not match the outer bound in general, special cases where they meet are identified. #R##N#In the case of a Gaussian MAC, a specialized achievable region is found by using a combination of dirty paper coding and a generalization of the Schalkwijk-Kailath, Ozarow and Merhav-Weissman schemes, and this region is found to be capacity achieving. Specifically, it is shown that additive Gaussian interference that is known non-causally to the transmitter causes no loss in capacity for the Gaussian MAC with feedback.

Connected through hyperedge HE-1 (induced by source paper "on continuous time gaussian channels"):
  with members:
    - "upper and lower bounds on the capacity of amplitude constrained mimo channels"
    - "recent results in continuous time network information theory"
    - "wireless network information flow a deterministic approach"
    - "limit theorems in hidden markov models"
    - "directed information causal estimation and communication in continuous time"
    - "feedback capacity of the gaussian interference channel to within 2 bits"
    - "on the gaussian mac with imperfect feedback"
    - "a new outer bound and the noisy interference sum rate capacity for gaussian interference channels"

Connected through hyperedge HE-2 (induced by source paper "capacity regions of families of continuous time multi user gaussian channels"):
  with members:
    - "extensions of the i mmse relation"
    - "recent results in continuous time network information theory"
    - "wireless network information flow a deterministic approach"
    - "on the gaussian mac with imperfect feedback"
    - "capacity bounds for the gaussian interference channel"
    - "gaussian interference channel capacity to within one bit"
    - "coding for the feedback gel fand pinsker channel and the feedforward wyner ziv source"
    - "mutual information and minimum mean square error in gaussian channels"

Connected through hyperedge HE-3 (induced by source paper "interference channel with generalized feedback a k a with source cooperation part i achievable region"):
  with members:
    - "dependence balance based outer bounds for gaussian networks with cooperation and feedback"
    - "interference channels with source cooperation"
    - "new inner and outer bounds for the discrete memoryless cognitive interference channel and some capacity results"
    - "feedback capacity of the gaussian interference channel to within 1 7075 bits the symmetric case"
    - "capacity bounds for the gaussian interference channel"
    - "gaussian interference channel capacity to within one bit"
    - "on the capacity of interference channels with one cooperating transmitter"

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)