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 information rate of mimo systems with finite rate channel state feedback using beamforming and power on off strategy"
  Abstract: It is well known that Multiple-Input Multiple-Output (MIMO) systems have high spectral efficiency, especially when channel state information at the transmitter (CSIT) is available. When CSIT is obtained by feedback, it is practical to assume that the channel state feedback rate is finite and the CSIT is not perfect. For such a system, we consider beamforming and power on/off strategy for its simplicity and near optimality, where power on/off means that a beamforming vector (beam) is either turned on with a constant power or turned off. The main contribution of this paper is to accurately evaluate the information rate as a function of the channel state feedback rate. Name a beam turned on as an on-beam and the minimum number of the transmit and receive antennas as the dimension of a MIMO system. We prove that the ratio of the optimal number of on-beams and the system dimension converges to a constant for a given signal-to-noise ratio (SNR) when the numbers of transmit and receive antennas approach infinity simultaneously and when beamforming is perfect. Asymptotic formulas are derived to evaluate this ratio and the corresponding information rate per dimension. The asymptotic results can be accurately applied to finite dimensional systems and suggest a power on/off strategy with a constant number of on-beams. For this suboptimal strategy, we take a novel approach to introduce power efficiency factor, which is a function of the feedback rate, to quantify the effect of imperfect beamforming. By combining power efficiency factor and the asymptotic formulas for perfect beamforming case, the information rate of the power on/off strategy with a constant number of on-beams is accurately characterized.

Connected through hyperedge HE-1 (induced by source paper "unequal dimensional small balls and quantization on grassmann manifolds"):
  with members:
    - "quantization bounds on grassmann manifolds of arbitrary dimensions and mimo communications with feedback"
    - "a feedback reduction technique for mimo broadcast 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)