human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "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.

Includes members:
  Member "statistical beamforming on the grassmann manifold for the two user broadcast channel":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "statistical beamforming for fdd downlink massive mimo via spatial information extraction and beam selection")
  Member "why does the kronecker model result in misleading capacity estimates":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "channel correlation diversity in mu mimo systems analysis and measurements")
  Member "capacity of a multiple antenna fading channel with a quantized precoding matrix":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "on optimizing feedback interval for temporally correlated mimo channels with transmit beamforming and finite rate feedback")
  Member "quantized multimode precoding in spatially correlated multiantenna channels":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "why does the kronecker model result in misleading capacity estimates")
  Member "multiuser mimo achievable rates with downlink training and channel state feedback":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "beyond dirty paper coding for multi antenna broadcast channel with partial csit a rate splitting approach")
  Member "mimo broadcast channels with finite rate feedback":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "dl based csi feedback and cooperative recovery in massive mimo")

Question: Please tell me which class the source paper 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)