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: "capacity of a multiple antenna fading channel with a quantized precoding matrix"
  Abstract: Given a multiple-input multiple-output (MIMO) channel, feedback from the receiver can be used to specify a transmit precoding matrix, which selectively activates the strongest channel modes. Here we analyze the performance of random vector quantization (RVQ), in which the precoding matrix is selected from a random codebook containing independent, isotropically distributed entries. We assume that channel elements are independent and identically distributed (i.i.d.) and known to the receiver, which relays the optimal (rate-maximizing) precoder codebook index to the transmitter using B bits. We first derive the large system capacity of beamforming (rank-one precoding matrix) as a function of B, where large system refers to the limit as B and the number of transmit and receive antennas all go to infinity with fixed ratios. RVQ for beamforming is asymptotically optimal, i.e., no other quantization scheme can achieve a larger asymptotic rate. We subsequently consider a precoding matrix with arbitrary rank, and approximate the asymptotic RVQ performance with optimal and linear receivers (matched filter and minimum mean squared error (MMSE)). Numerical examples show that these approximations accurately predict the performance of finite-size systems of interest. Given a target spectral efficiency, numerical examples show that the amount of feedback required by the linear MMSE receiver is only slightly more than that required by the optimal receiver, whereas the matched filter can require significantly more feedback.

Connected through hyperedge HE-1 (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"
    - "ensemble properties of rvq based limited feedback beamforming codebooks"
    - "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"
    - "limited feedback beamforming over temporally correlated channels"

Connected through hyperedge HE-2 (induced by source paper "perfect secrecy in physical layer network coding systems from structured interference"):
  with members:
    - "secure compute and forward in a bidirectional relay"
    - "secure degrees of freedom of one hop wireless networks"
    - "feasibility of interference alignment for the mimo interference channel"
    - "strong secrecy in wireless network coding systems with m qam modulators"
    - "five disruptive technology directions for 5g"
    - "degrees of freedom for the mimo multi way relay channel"
    - "reliable physical layer network coding"
    - "interference alignment for secrecy"

Connected through hyperedge HE-3 (induced by source paper "queueing stability and csi probing of a tdd wireless network with interference alignment"):
  with members:
    - "performance analysis and optimization for interference alignment over mimo interference channels with limited feedback"
    - "csit sharing over finite capacity backhaul for spatial interference alignment"
    - "performance evaluation of multiterminal backhaul compression for cloud radio access networks"
    - "on feasibility of interference alignment in mimo interference networks"
    - "interference alignment with analog channel state feedback"
    - "interference alignment under limited feedback for mimo interference channels"
    - "interference alignment with limited feedback"
    - "stability and delay of zero forcing sdma with limited feedback"

Connected through hyperedge HE-4 (induced by source paper "on transmit beamforming for miso ofdm channels with finite rate feedback"):
  with members:
    - "power scaling of uplink massive mimo systems with arbitrary rank channel means"

Connected through hyperedge HE-5 (induced by source paper "joint wireless information and energy transfer with reduced feedback in mimo interference channels"):
  with members:
    - "simultaneous information and power transfer for broadband wireless systems"
    - "wireless information and power transfer in multiuser ofdm systems"
    - "relaying protocols for wireless energy harvesting and information processing"
    - "optimal scheduling and power allocation for two hop energy harvesting communication systems"
    - "wireless information transfer with opportunistic energy harvesting"
    - "multi user diversity vs accurate channel state information in mimo downlink channels"
    - "enabling wireless power transfer in cellular networks architecture modeling and deployment"
    - "robust beamforming for wireless information and power transmission"

Connected through hyperedge HE-6 (induced by source paper "trellis extended codebooks and successive phase adjustment a path from lte advanced to fdd massive mimo systems"):
  with members:
    - "pilot beam pattern design for channel estimation in massive mimo systems"
    - "bounds on eigenvalues of a spatial correlation matrix"
    - "downlink training techniques for fdd massive mimo systems open loop and closed loop training with memory"
    - "noncoherent trellis coded quantization a practical limited feedback technique for massive mimo systems"
    - "optimal feedback rate sharing strategy in zero forcing mimo broadcast channels"
    - "scaling up mimo opportunities and challenges with very large arrays"
    - "mimo broadcast channels with finite rate feedback"
    - "limited feedback beamforming over temporally correlated channels"

Connected through hyperedge HE-7 (induced by source paper "guaranteeing positive secrecy capacity with finite rate feedback using artificial noise"):
  with members:
    - "artificial noise revisited"
    - "limited feedback based block diagonalization for the mimo broadcast channel"
    - "the secrecy capacity of the mimo wiretap channel"
    - "quantization bounds on grassmann manifolds and applications to mimo communications"

Connected through hyperedge HE-8 (induced by source paper "noncoherent trellis coded quantization a practical limited feedback technique for massive mimo systems"):
  with members:
    - "downlink training techniques for fdd massive mimo systems open loop and closed loop training with memory"
    - "scaling up mimo opportunities and challenges with very large arrays"
    - "massive mimo how many antennas do we need"
    - "energy and spectral efficiency of very large multiuser mimo systems"
    - "glrt optimal noncoherent lattice decoding"
    - "mimo broadcast channels with finite rate feedback"
    - "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)