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: "a compressive channel estimation technique robust to synchronization impairments"
  Abstract: Initial access at millimeter wave frequencies is a challenging problem due to hardware non-idealities and low SNR measurements prior to beamforming. Prior work has exploited the observation that mmWave MIMO channels are sparse in the spatial angle domain and has used compressed sensing based algorithms for channel estimation. Most of them, however, ignore hardware impairments like carrier frequency offset and phase noise, and fail to perform well when such impairments are considered. In this paper, we develop a compressive channel estimation algorithm for narrowband mmWave systems, which is robust to such non idealities. We address this problem by constructing a tensor that models both the mmWave channel and CFO, and estimate the tensor while still exploiting the sparsity of the mmWave channel. Simulation results show that under the same settings, our method performs better than comparable algorithms that are robust to phase errors.

Connected through hyperedge HE-1 (induced by source paper "swift link a compressive beam alignment algorithm for practical mmwave radios"):
  with members:
    - "partially blind handovers for mmwave new radio aided by sub 6 ghz lte signaling"
    - "a novel millimeter wave channel simulator and applications for 5g wireless communications"
    - "compressive channel estimation and tracking for large arrays in mm wave picocells"
    - "hierarchical codebook design for beamforming training in millimeter wave communication"
    - "an overview of signal processing techniques for millimeter wave mimo systems"
    - "hybrid architectures with few bit adc receivers achievable rates and energy rate tradeoffs"
    - "channel estimation in broadband millimeter wave mimo systems with few bit adcs"
    - "self calibration and biconvex compressive sensing"

Connected through hyperedge HE-2 (induced by source paper "message passing based joint cfo and channel estimation in millimeter wave systems with one bit adcs"):
  with members:
    - "partially blind handovers for mmwave new radio aided by sub 6 ghz lte signaling"
    - "joint cfo and channel estimation in millimeter wave systems with one bit adcs"
    - "compressive channel estimation and tracking for large arrays in mm wave picocells"
    - "bayes optimal joint channel and data estimation for massive mimo with low precision adcs"
    - "parametric bilinear generalized approximate message passing"
    - "an overview of signal processing techniques for millimeter wave mimo systems"
    - "channel estimation for hybrid architecture based wideband millimeter wave systems"
    - "channel estimation in broadband millimeter wave mimo systems with few bit adcs"

Connected through hyperedge HE-3 (induced by source paper "beam discovery using linear block codes for millimeter wave communication networks"):
  with members:
    - "agile millimeter wave networks with provable guarantees"
    - "millimeter wave mimo channel estimation based on adaptive compressed sensing"
    - "linear block coding for efficient beam discovery in millimeter wave communication networks"
    - "efficient beam alignment in millimeter wave systems using contextual bandits"
    - "millimeter wave mimo channel estimation using overlapped beam patterns and rate adaptation"
    - "an overview of signal processing techniques for millimeter wave mimo systems"
    - "low power analog to digital conversion in millimeter wave systems impact of resolution and bandwidth on performance"
    - "compressed sensing for wireless communications useful tips and tricks"

Connected through hyperedge HE-4 (induced by source paper "linear block coding for efficient beam discovery in millimeter wave communication networks"):
  with members:
    - "agile millimeter wave networks with provable guarantees"
    - "millimeter wave mimo channel estimation based on adaptive compressed sensing"
    - "millimeter wave mimo channel estimation using overlapped beam patterns and rate adaptation"
    - "an overview of signal processing techniques for millimeter wave mimo systems"
    - "low power analog to digital conversion in millimeter wave systems impact of resolution and bandwidth on performance"
    - "compressed sensing for wireless communications useful tips and tricks"
    - "compressed sensing based multi user millimeter wave systems how many measurements are needed"
    - "channel estimation and hybrid precoding for millimeter wave cellular systems"

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)