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: "training sequence design for feedback assisted hybrid beamforming in massive mimo systems"
  Abstract: The use of large-scale antenna systems in future commercial wireless communications is an emerging technology that uses an excess of transmit antennas to realize high spectral efficiency. Achieving potential gains with large-scale antenna arrays in practice hinges on sufficient channel estimation accuracy. Much prior work focuses on TDD based networks, relying on reciprocity between the uplink and downlink channels. However, most currently deployed commercial wireless systems are FDD based, making it difficult to exploit channel reciprocity. In massive MIMO FDD systems, the problem of channel estimation becomes even more challenging due to the attendant substantial training resources and feedback requirements which scale with the number of antennas. In this paper, we consider the problem of training sequence design that employs a set of training signals and its mapping to the training periods. We focus on reduced-dimension training sequence designs, along with transmit precoder designs, aimed at reducing both hardware complexity and power consumption. The resulting designs are extended to hybrid analog-digital beamforming systems, which employ a limited number of active RF chains for transmit precoding, by applying the Toeplitz distribution theorem to large-scale linear antenna systems. A practical guideline for training sequence parameter selection is presented along with performance analysis.

Connected through hyperedge HE-1 (induced by source paper "time varying downlink channel tracking for quantized massive mimo networks"):
  with members:
    - "beamspace aware adaptive channel estimation for single carrier time varying massive mimo channels"
    - "interference alignment and soft space reuse based cooperative transmission for multi cell massive mimo networks"
    - "bayesian optimal data detector for mmwave ofdm system with low resolution adc"
    - "a gamp based low complexity sparse bayesian learning algorithm"
    - "mixed adc massive mimo detectors performance analysis and design optimization"
    - "uplink achievable rate for massive mimo systems with low resolution adc"
    - "spatially common sparsity based adaptive channel estimation and feedback for fdd massive mimo"
    - "two tier precoding for fdd multi cell massive mimo time varying interference networks"

Connected through hyperedge HE-2 (induced by source paper "time varying massive mimo channel estimation capturing reconstruction and restoration"):
  with members:
    - "efficient downlink channel reconstruction for fdd multi antenna systems"
    - "channel estimation for tdd fdd massive mimo systems with channel covariance computing"
    - "interference alignment and soft space reuse based cooperative transmission for multi cell massive mimo networks"
    - "channel acquisition for massive mimo ofdm with adjustable phase shift pilots"
    - "design and implementation of a tdd based 128 antenna massive mimo prototyping system"
    - "uplink achievable rate for massive mimo systems with low resolution adc"
    - "spatially common sparsity based adaptive channel estimation and feedback for fdd massive mimo"
    - "millimeter wave mimo with lens antenna array a new path division multiplexing paradigm"

Connected through hyperedge HE-3 (induced by source paper "hybrid precoding architecture for massive multiuser mimo with dissipation sub connected or fully connected structures"):
  with members:
    - "on performance of quantized transceiver in multiuser massive mimo downlinks"
    - "spectral and energy efficiency of multi pair massive mimo relay network with hybrid processing"
    - "multiuser millimeter wave beamforming strategies with quantized and statistical csit"
    - "two dimensional aod and aoa acquisition for wideband millimeter wave systems with dual polarized mimo"
    - "hybrid analog digital precoding revisited under realistic rf modeling"
    - "alternating minimization algorithms for hybrid precoding in millimeter wave mimo systems"
    - "an overview of signal processing techniques for millimeter wave mimo systems"
    - "linear precoding of data and artificial noise in secure massive mimo systems"

Connected through hyperedge HE-4 (induced by source paper "on the energy efficiency of mimo hybrid beamforming for millimeter wave systems with nonlinear power amplifiers"):
  with members:
    - "spatial characteristics of distortion radiated from antenna arrays with transceiver nonlinearities"
    - "codebook based hybrid precoding for millimeter wave multiuser systems"
    - "common codebook millimeter wave beam design designing beams for both sounding and communication with uniform planar arrays"
    - "spectrum sharing in mmwave cellular networks via cell association coordination and beamforming"
    - "waveforms for the massive mimo downlink amplifier efficiency distortion and performance"
    - "hybrid mimo architectures for millimeter wave communications phase shifters or switches"
    - "channel estimation and hybrid precoding for millimeter wave cellular systems"
    - "massive mimo systems with non ideal hardware energy efficiency estimation and capacity limits"

Connected through hyperedge HE-5 (induced by source paper "channel reconstruction based hybrid precoding for millimeter wave multi user mimo systems"):
  with members:
    - "millimeter wave mimo prototype measurements and experimental results"
    - "common codebook millimeter wave beam design designing beams for both sounding and communication with uniform planar arrays"
    - "directional beamforming for millimeter wave mimo systems"
    - "investigation of prediction accuracy sensitivity and parameter stability of large scale propagation path loss models for 5g wireless communications"
    - "on the number of rf chains and phase shifters and scheduling design with hybrid analog digital beamforming"
    - "hybrid digital and analog beamforming design for large scale antenna arrays"
    - "beamforming tradeoffs for initial ue discovery in millimeter wave mimo systems"
    - "limited feedback hybrid precoding for multi user millimeter wave systems"

Connected through hyperedge HE-6 (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"
    - "antenna grouping based feedback compression for fdd based massive mimo systems"
    - "distributed compressive csit estimation and feedback for fdd multi user 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-7 (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"
    - "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"
    - "capacity of a multiple antenna fading channel with a quantized precoding matrix"
    - "limited feedback beamforming over temporally correlated channels"

Connected through hyperedge HE-8 (induced by source paper "noisy beam alignment techniques for reciprocal mimo channels"):
  with members:
    - "subspace estimation and decomposition for large millimeter wave mimo systems"
    - "beamforming tradeoffs for initial ue discovery in millimeter wave mimo systems"
    - "channel estimation and hybrid precoding for millimeter wave cellular systems"
    - "what will 5g be"
    - "millimeter wave cellular wireless networks potentials and challenges"
    - "downlink training techniques for fdd massive mimo systems open loop and closed loop training with memory"
    - "spatially sparse precoding in millimeter wave mimo systems"
    - "five disruptive technology directions for 5g"

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)