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 symmetric feedback capacity of the k user cyclic interference channel"
  Abstract: The K-user cyclic interference channel models a situation in which the kth transmitter causes interference only to the (k − 1)mod(K)th receiver. The impact of noiseless feedback on the capacity of this channel is studied by focusing on the linear shift deterministic cyclic interference channel (LD-CIC). For the case of symmetric channel parameters, the symmetric feedback capacity is characterized for all interference regimes. It is shown that the symmetric feedback capacity is in general a function of K, the number of users. Furthermore, the capacity gain obtained due to feedback decreases as K increases.

Connected through hyperedge HE-1 (induced by source paper "an outer bound for the memoryless two user interference channel with general cooperation"):
  with members:
    - "two way interference channels"
    - "inner and outer bounds for the gaussian cognitive interference channel and new capacity results"
    - "dependence balance based outer bounds for gaussian networks with cooperation and feedback"
    - "a new sum rate outer bound for interference channels with three source destination pairs"
    - "interference channels with source cooperation"
    - "interference channels with rate limited feedback"
    - "interference channels with destination cooperation"
    - "interference mitigation through limited transmitter cooperation"

Connected through hyperedge HE-2 (induced by source paper "close form design of antenna constrained multi cell multi user downlink interference alignment"):
  with members:
    - "on the sum capacity of k user cascade gaussian z interference channel"
    - "downlink interference alignment"
    - "on the capacity of the k user cyclic gaussian interference channel"
    - "interference alignment under limited feedback for mimo interference channels"
    - "approaching the capacity of wireless networks through distributed interference alignment"
    - "multiuser mimo achievable rates with downlink training and channel state feedback"

Connected through hyperedge HE-3 (induced by source paper "on the feedback capacity of the fully connected k user interference channel"):
  with members:
    - "capacity of all nine models of channel output feedback for the two user interference channel"
    - "the approximate sum capacity of the symmetric gaussian k user interference channel"
    - "dependence balance based outer bounds for gaussian networks with cooperation and feedback"
    - "feedback capacity of the gaussian interference channel to within 2 bits"
    - "lecture notes on network information theory"
    - "the two user gaussian interference channel a deterministic view"
    - "generalized degrees of freedom of the symmetric gaussian k user interference channel"
    - "transmission techniques for relay interference networks"

Connected through hyperedge HE-4 (induced by source paper "on the capacity of the k user cyclic gaussian interference channel"):
  with members:
    - "the approximate sum capacity of the symmetric gaussian k user interference channel"
    - "a new sum rate outer bound for interference channels with three source destination pairs"
    - "the approximate capacity of the many to one and one to many gaussian interference channels"
    - "the capacity region of the 3 user gaussian interference channel with mixed strong very strong interference"
    - "interference alignment and a noisy interference regime for many to one interference channels"
    - "a new outer bound and the noisy interference sum rate capacity for gaussian interference channels"
    - "capacity bounds for the gaussian interference channel"
    - "generalized degrees of freedom of the symmetric gaussian k user interference channel"

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)