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: "ensemble properties of rvq based limited feedback beamforming codebooks"
  Abstract: The ensemble properties of Random Vector Quantization (RVQ) codebooks for limited-feedback beamforming in multi-input multi-output (MIMO) systems are studied with the metrics of interest being the received SNR loss and mutual information loss, both relative to a perfect channel state information (CSI) benchmark. The simplest case of unskewed codebooks is studied in the correlated MIMO setting and these loss metrics are computed as a function of the number of bits of feedback ($B$), transmit antenna dimension ($N_t$), and spatial correlation. In particular, it is established that: i) the loss metrics are a product of two components -- a quantization component and a channel-dependent component; ii) the quantization component, which is also common to analysis of channels with independent and identically distributed (i.i.d.) fading, decays as $B$ increases at the rate $2^{-B/(N_t-1)}$; iii) the channel-dependent component reflects the condition number of the channel. Further, the precise connection between the received SNR loss and the squared singular values of the channel is shown to be a Schur-convex majorization relationship. Finally, the ensemble properties of skewed codebooks that are generated by skewing RVQ codebooks with an appropriately designed fixed skewing matrix are studied. Based on an estimate of the loss expression for skewed codebooks, it is established that the optimal skewing matrix is critically dependent on the condition numbers of the effective channel (product of the true channel and the skewing matrix) and the skewing matrix.

Connected through hyperedge HE-1 (induced by source paper "clustering based codebook design for mimo communication system"):
  with members:
    - "deep learning based csi feedback approach for time varying massive mimo channels"
    - "deep learning for wireless physical layer opportunities and challenges"
    - "channel estimation for tdd fdd massive mimo systems with channel covariance computing"
    - "deep learning for massive mimo csi feedback"
    - "limited feedback hybrid precoding for multi user millimeter wave systems"
    - "scaling up mimo opportunities and challenges with very large arrays"

Connected through hyperedge HE-2 (induced by source paper "hybrid beamforming with selection for multiuser massive mimo systems"):
  with members:
    - "stationarity region of mm wave channel based on outdoor microcellular measurements at 28 ghz"
    - "alternating minimization algorithms for hybrid precoding in millimeter wave mimo systems"
    - "5g 3gpp like channel models for outdoor urban microcellular and macrocellular environments"
    - "an overview of signal processing techniques for millimeter wave mimo systems"
    - "hybrid digital and analog beamforming design for large scale antenna arrays"
    - "massive mimo combining with switches"
    - "hybrid beamforming for massive mimo a survey"
    - "analysis of the local quasi stationarity of measured dual polarized mimo channels"

Connected through hyperedge HE-3 (induced by source paper "on optimizing feedback interval for temporally correlated mimo channels with transmit beamforming and finite rate feedback"):
  with members:
    - "on transmit beamforming for miso ofdm channels with finite rate feedback"
    - "training sequence design for feedback assisted hybrid beamforming in massive mimo systems"
    - "tree structured random vector quantization for limited feedback wireless channels"
    - "on the minimum differential feedback for time correlated mimo rayleigh block fading channels"
    - "optimization of training and feedback overhead for beamforming over block fading channels"
    - "capacity of a multiple antenna fading channel with a quantized precoding matrix"
    - "limited feedback beamforming over temporally correlated channels"

Connected through hyperedge HE-4 (induced by source paper "a time variant channel prediction and feedback framework for interference alignment"):
  with members:
    - "on the degrees of freedom for opportunistic interference alignment with 1 bit feedback the 3 cell case"
    - "delay and doppler spreads of nonstationary vehicular channels for safety relevant scenarios"
    - "grassmannian differential limited feedback for interference alignment"
    - "adaptive interference alignment with csi uncertainty"
    - "optimization of training and feedback overhead for beamforming over block fading channels"
    - "interference alignment with analog channel state feedback"
    - "interference alignment under limited feedback for mimo interference channels"
    - "multiuser mimo achievable rates with downlink training and channel state feedback"

Connected through hyperedge HE-5 (induced by source paper "achievable rates of fdd massive mimo systems with spatial channel correlation"):
  with members:
    - "fundamental limits in correlated fading mimo broadcast channels benefits of transmit correlation diversity"
    - "massive mimo systems with non ideal hardware energy efficiency estimation and capacity limits"
    - "distributed compressive csit estimation and feedback for fdd multi user massive mimo systems"
    - "downlink training techniques for fdd massive mimo systems open loop and closed loop training with memory"
    - "blind pilot decontamination"
    - "aligned image sets under channel uncertainty settling a conjecture by lapidoth shamai and wigger on the collapse of degrees of freedom under finite precision csit"
    - "trellis extended codebooks and successive phase adjustment a path from lte advanced to fdd massive mimo systems"
    - "noncoherent trellis coded quantization a practical limited feedback technique for massive mimo systems"

Connected through hyperedge HE-6 (induced by source paper "bounds on eigenvalues of a spatial correlation matrix"):
  with members:
    - "kronecker product correlation model and limited feedback codebook design in a 3d channel model"
    - "downlink training techniques for fdd massive mimo systems open loop and closed loop training with memory"
    - "statistical beamforming on the grassmann manifold for the two user broadcast channel"
    - "scaling up mimo opportunities and challenges with very large arrays"

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)