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: "antenna grouping based feedback compression for fdd based massive mimo systems"
  Abstract: Recent works on massive multiple-input multiple-output (MIMO) have shown that a potential breakthrough in capacity gains can be achieved by deploying a very large number of antennas at the base station. In order to achieve the performance that massive MIMO systems promise, accurate transmit-side channel state information (CSI) should be available at the base station. While transmit-side CSI can be obtained by employing channel reciprocity in time division duplexing (TDD) systems, explicit feedback of CSI from the user terminal to the base station is needed for frequency division duplexing (FDD) systems. In this paper, we propose an antenna grouping based feedback reduction technique for FDD-based massive MIMO systems. The proposed algorithm, dubbed antenna group beamforming (AGB), maps multiple correlated antenna elements to a single representative value using predesigned patterns. The proposed method modifies the feedback packet by introducing the concept of a  header  to select a suitable group pattern and a  payload  to quantize the reduced dimension channel vector. Simulation results show that the proposed method achieves significant feedback overhead reduction over conventional approach performing the vector quantization of whole channel vector under the same target sum rate requirement.

Connected through hyperedge HE-1 (induced by source paper "a covariance based hybrid channel feedback in fdd massive mimo systems"):
  with members:
    - "downlink precoding with mixed statistical and imperfect instantaneous csi for massive mimo systems"
    - "fdd massive mimo via ul dl channel covariance extrapolation and active channel sparsification"
    - "channel feedback based on aod adaptive subspace codebook in fdd massive mimo systems"
    - "enabling covariance based feedback in massive mimo a user classification approach"
    - "channel estimation for tdd fdd massive mimo systems with channel covariance computing"
    - "pilot power allocation through user grouping in multi cell massive mimo systems"
    - "spatially common sparsity based adaptive channel estimation and feedback for fdd massive mimo"
    - "dealing with interference in distributed large scale mimo systems a statistical approach"

Connected through hyperedge HE-2 (induced by source paper "downlink pilot precoding and compressed channel feedback for fdd based cell free systems"):
  with members:
    - "channel feedback based on aod adaptive subspace codebook in fdd massive mimo systems"
    - "on the total energy efficiency of cell free massive mimo"
    - "joint channel training and feedback for fdd massive mimo systems"
    - "cell free massive mimo versus small cells"
    - "power allocation schemes for multicell massive mimo systems"
    - "downlink training techniques for fdd massive mimo systems open loop and closed loop training with memory"
    - "pilot contamination and precoding in multi cell tdd systems"
    - "mimo broadcast channels with finite rate feedback"

Connected through hyperedge HE-3 (induced by source paper "on optimal scheduling for joint spatial division and multiplexing approach in fdd massive mimo"):
  with members:
    - "graph theory based approach to users grouping and downlink scheduling in fdd massive mimo"
    - "fdd massive mimo efficient downlink probing and uplink feedback via active channel sparsification"
    - "efficient downlink channel probing and uplink feedback in fdd massive mimo systems"
    - "content aware user clustering and caching in wireless small cell networks"
    - "scaling up mimo opportunities and challenges with very large arrays"
    - "large system analysis of linear precoding in correlated miso broadcast channels under limited feedback"
    - "energy and spectral efficiency of very large multiuser mimo systems"

Connected through hyperedge HE-4 (induced by source paper "interleaving channel estimation and limited feedback for point to point systems with a large number of transmit antennas"):
  with members:
    - "interleaved training and training based transmission design for hybrid massive antenna downlink"
    - "compressed channel feedback for correlated massive mimo systems"
    - "spatially common sparsity based adaptive channel estimation and feedback for fdd massive mimo"
    - "distributed compressive csit estimation and feedback for fdd multi user massive mimo systems"
    - "training sequence design for feedback assisted hybrid beamforming in massive mimo systems"
    - "massive mimo for next generation wireless systems"
    - "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"

Connected through hyperedge HE-5 (induced by source paper "channel feedback based on aod adaptive subspace codebook in fdd massive mimo systems"):
  with members:
    - "limited feedback channel estimation in massive mimo with non uniform directional dictionaries"
    - "joint channel training and feedback for fdd massive mimo systems"
    - "channel estimation for hybrid architecture based wideband millimeter wave systems"
    - "compressed channel feedback for correlated massive mimo systems"
    - "the impact of beamwidth on temporal channel variation in vehicular channels and its implications"
    - "channel estimation and hybrid precoding for millimeter wave cellular systems"
    - "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"

Connected through hyperedge HE-6 (induced by source paper "cooperative limited feedback design for massive machine type communications"):
  with members:
    - "advanced quantizer designs for fdd based fd mimo systems using uniform planar arrays"
    - "exploiting trust degree for multiple antenna user cooperation"
    - "five disruptive technology directions for 5g"
    - "multi user diversity vs accurate channel state information in mimo downlink channels"
    - "interference alignment through user cooperation for two cell mimo interfering broadcast channels"
    - "antenna combining for the mimo downlink channel"

Connected through hyperedge HE-7 (induced by source paper "distributed base station a concept system for long range broadband wireless access"):
  with members:
    - "a scalable architecture for distributed receive beamforming analysis and experimental demonstration"
    - "high dimensional csi acquisition in massive mimo sparsity inspired approaches"
    - "massive mimo for next generation wireless systems"
    - "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"
    - "airsync enabling distributed multiuser mimo with full spatial multiplexing"

Connected through hyperedge HE-8 (induced by source paper "regularized zero forcing precoding aided adaptive coding and modulation for large scale antenna array based air to air communications"):
  with members:
    - "impact of line of sight and unequal spatial correlation on uplink mu mimo systems"
    - "adaptive coding and modulation for large scale antenna array based aeronautical communications in the presence of co channel interference"
    - "asymptotic analysis of multicell massive mimo over rician fading channels"
    - "massive mimo for next generation wireless systems"
    - "large system analysis of cooperative multi cell downlink transmission via regularized channel inversion with imperfect csit"

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)