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: "event driven optimal feedback control for multiantenna beamforming"
  Abstract: Transmit beamforming is a simple multiantenna technique for increasing throughput and the transmission range of a wireless communication system. The required feedback of channel state information (CSI) can potentially result in excessive overhead especially for high mobility or many antennas. This work concerns efficient feedback for transmit beamforming and establishes a new approach of controlling feedback for maximizing throughput under a constraint on the average feedback rate. The feedback controller using a stationary policy turns CSI feedback on/off according to the system state that comprises the channel state and transmit beamformer. Assuming channel isotropy and Markovity, the controller's state reduces to two scalars. This allows the optimal control policy to be efficiently computed using dynamic programming. Consider the unquantized feedback channel free of error, where each feedback instant pays a fixed price. The corresponding optimal feedback control policy is proved to be of the threshold type. This result holds regardless of whether the controller's state space is discretized or continuous. Under the threshold-type policy, feedback is performed whenever a state variable indicating the accuracy of transmit CSI is below a threshold, which varies with channel power. The practical quantized feedback channel is also considered. The optimal policy for quantized feedback is proved to be also of the threshold type. The effect of CSI quantization is shown to be equivalent to an increment on the feedback price. Moreover, the increment is upper bounded by the expected logarithm of one minus the quantization error. Finally, simulation shows that feedback control increases throughput of the conventional periodic feedback by up to 0.5 bit/s/Hz without requiring additional bandwidth or antennas.

Connected through hyperedge HE-1 (induced by source paper "stochastic control of event driven feedback in multiantenna interference channels"):
  with members:
    - "multi antenna communication in ad hoc networks achieving mimo gains with simo transmission"
    - "adaptive bit partitioning for multicell intercell interference nulling with delayed limited feedback"
    - "cooperative feedback for multi antenna cognitive radio networks"
    - "interference alignment with limited feedback"
    - "grassmannian beamforming for mimo amplify and forward relaying"
    - "space division multiple access with a sum feedback rate constraint"
    - "interference alignment and the degrees of freedom for the k user interference channel"
    - "mimo broadcast channels with finite rate feedback"

Connected through hyperedge HE-2 (induced by source paper "cooperative precoding with limited feedback for mimo interference channels"):
  with members:
    - "cooperative interference management with miso beamforming"
    - "cooperative feedback for multi antenna cognitive radio networks"
    - "limited feedback based block diagonalization for the mimo broadcast channel"
    - "interference alignment and the degrees of freedom for the k user interference channel"
    - "mimo broadcast channels with finite rate feedback"
    - "performance of orthogonal beamforming for sdma with limited feedback"
    - "quantization bounds on grassmann manifolds and applications to mimo communications"
    - "limited feedback beamforming over temporally correlated channels"

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)