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: "low rank spatial channel estimation for millimeter wave cellular systems"
  Abstract: The tremendous bandwidth available in the millimeter wave (mmW) frequencies between 30 and 300 GHz have made these bands an attractive candidate for next-generation cellular systems. However, reliable communication at these frequencies depends extensively on beamforming with very high-dimensional antenna arrays. Estimating the channel sufficiently accurately to perform beamforming can thus be challenging both due to low coherence time and large number of antennas. Also, the measurements used for channel estimation may need to be made with analog beamforming where the receiver can "look" in only direction at a time. This work presents a novel method for estimation of the receive-side spatial covariance matrix of a channel from a sequence of power measurements made at different angular directions. The method reduces the spatial covariance estimation to a matrix completion optimization problem. To reduce the number of measurements, the optimization can incorporate the low-rank constraints in the channels that are typical in the mmW setting. The optimization is convex and fast, iterative methods are presented to solving the problem. Simulations are presented for both single and multi-path channels using channel models derived from real measurements in New York City at 28 GHz.

Connected through hyperedge HE-1 (induced by source paper "deep learning for massive mimo channel state acquisition and feedback"):
  with members:
    - "deep learning for massive mimo with 1 bit adcs when more antennas need fewer pilots"
    - "deep learning based channel estimation for massive mimo with mixed resolution adcs"
    - "cnn based analog csi feedback in fdd mimo ofdm systems"
    - "deep learning for tdd and fdd massive mimo mapping channels in space and frequency"
    - "deepmimo a generic deep learning dataset for millimeter wave and massive mimo applications"
    - "multi resolution csi feedback with deep learning in massive mimo system"
    - "deep convolutional compression for massive mimo csi feedback"
    - "machine learning in the air"

Connected through hyperedge HE-2 (induced by source paper "a new insight into gamp and amp"):
  with members:
    - "capacity achieving mimo noma iterative lmmse detection"
    - "capacity optimality of amp in coded systems"
    - "a unified bayesian inference framework for generalized linear models"
    - "bilinear adaptive generalized vector approximate message passing"
    - "gaussian message passing for overloaded massive mimo noma"
    - "massive connectivity with massive mimo part i device activity detection and channel estimation"
    - "beam on graph simultaneous channel estimation for mmwave mimo systems with multiple users"
    - "rigorous dynamics of expectation propagation based signal recovery from unitarily invariant measurements"

Connected through hyperedge HE-3 (induced by source paper "fully partially connected hybrid beamforming architectures for mmwave mu mimo"):
  with members:
    - "hybrid precoding architecture for massive multiuser mimo with dissipation sub connected or fully connected structures"
    - "on the energy efficiency of mimo hybrid beamforming for millimeter wave systems with nonlinear power amplifiers"
    - "hybrid beamforming based on implicit channel state information for millimeter wave links"
    - "fully connected vs sub connected hybrid precoding architectures for mmwave mu mimo"
    - "millimeter wave mimo prototype measurements and experimental results"
    - "hybrid analog digital beamforming for massive mimo systems"
    - "frequency domain compressive channel estimation for frequency selective hybrid mmwave mimo systems"
    - "a robust time domain beam alignment scheme for multi user wideband mmwave systems"

Connected through hyperedge HE-4 (induced by source paper "end to end simulation of 5g mmwave networks"):
  with members:
    - "integration of carrier aggregation and dual connectivity for the ns 3 mmwave module"
    - "x tcp a cross layer approach for tcp uplink flows in mmwave networks"
    - "enhancing tcp end to end performance in millimeter wave communications"
    - "beam alignment for millimetre wave links with motion prediction of autonomous vehicles"
    - "tcp in 5g mmwave networks link level retransmissions and mp tcp"
    - "provisioning low latency resilient mobile edge clouds for 5g"
    - "caching meets millimeter wave communications for enhanced mobility management in 5g networks"
    - "reliable video streaming over mmwave with multi connectivity and network coding"

Connected through hyperedge HE-5 (induced by source paper "efficient beam alignment for mmwave single carrier systems with hybrid mimo transceivers"):
  with members:
    - "single carrier modulation versus ofdm for millimeter wave wireless mimo"
    - "throughput optimal beam alignment in millimeter wave networks"
    - "frequency domain compressive channel estimation for frequency selective hybrid mmwave mimo systems"
    - "on the ergodic rate lower bounds with applications to massive mimo"
    - "millimeter wave mimo channel estimation using overlapped beam patterns and rate adaptation"
    - "a robust time domain beam alignment scheme for multi user wideband mmwave systems"
    - "robust nonnegative sparse recovery and the nullspace property of 0 1 measurements"
    - "channel estimation for hybrid architecture based wideband millimeter wave systems"

Connected through hyperedge HE-6 (induced by source paper "hybrid precoding for massive mimo systems in cloud ran architecture with capacity limited fronthauls"):
  with members:
    - "layered downlink precoding for c ran systems with full dimensional mimo"
    - "an overview of signal processing techniques for millimeter wave mimo systems"
    - "recent advances in cloud radio access networks system architectures key techniques and open issues"
    - "on the number of rf chains and phase shifters and scheduling design with hybrid analog digital beamforming"
    - "channel covariance estimation in massive mimo frequency division duplex systems"
    - "hybrid beamforming for massive mimo a survey"
    - "regularized zf in cooperative broadcast channels under distributed csit a large system analysis"
    - "limited feedback hybrid precoding for multi user millimeter wave systems"

Connected through hyperedge HE-7 (induced by source paper "millimeter wave receiver efficiency a comprehensive comparison of beamforming schemes with low resolution adcs"):
  with members:
    - "millimeter wave receiver comparison under energy vs spectral efficiency trade off"
    - "throughput analysis of massive mimo uplink with low resolution adcs"
    - "uplink performance of wideband massive mimo with one bit adcs"
    - "on the spectral efficiency of massive mimo systems with low resolution adcs"
    - "hybrid architectures with few bit adc receivers achievable rates and energy rate tradeoffs"
    - "towards an appropriate receiver beamforming scheme for millimeter wave communication a power consumption based comparison"
    - "low power analog to digital conversion in millimeter wave systems impact of resolution and bandwidth on performance"
    - "one bit massive mimo channel estimation and high order modulations"

Connected through hyperedge HE-8 (induced by source paper "low complexity channel estimation for millimeter wave systems with hybrid a d antenna processing"):
  with members:
    - "compressive channel estimation and tracking for large arrays in mm wave picocells"
    - "channel estimation and hybrid precoding for millimeter wave cellular systems"
    - "what will 5g be"
    - "millimeter wave mimo channel tracking systems"
    - "five disruptive technology directions for 5g"
    - "millimeter wave beamforming for wireless backhaul and access in small cell networks"
    - "iterative hard thresholding for compressed sensing"

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)