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: "super resolution delay doppler estimation for ofdm passive radar"
  Abstract: In this paper, we consider the problem of joint delay-Doppler estimation of moving targets in a passive radar that makes use of orthogonal frequency-division multiplexing communication signals. A compressed sensing algorithm is proposed to achieve supper resolution and better accuracy, using both the atomic norm and the $\ell _1$-norm. The atomic norm is used to manifest the signal sparsity in the continuous domain. Unlike previous works that assume the demodulation to be error free, we explicitly introduce the demodulation error signal whose sparsity is imposed by the $\ell _1$-norm. On this basis, the delays and Doppler frequencies are estimated by solving a semidefinite program (SDP) which is convex. We also develop an iterative method for solving this SDP via the alternating direction method of multipliers where each iteration involves closed-form computation. Simulation results are presented to illustrate the high performance of the proposed algorithm.

Connected through hyperedge HE-1 (induced by source paper "multi dimensional spectral super resolution with prior knowledge via frequency selective vandermonde decomposition and admm"):
  with members:
    - "multi target position and velocity estimation using ofdm communication signals"
    - "adaptive interference removal for uncoordinated radar communication coexistence"
    - "recovery of structured signals with prior information via maximizing correlation"
    - "near optimal sample complexity for convex tensor completion"
    - "millimeter wave beamformed full dimensional mimo channel estimation based on atomic norm minimization"
    - "rank determination for low rank data completion"
    - "characterization of deterministic and probabilistic sampling patterns for finite completability of low tensor train rank tensor"
    - "frequency selective vandermonde decomposition of toeplitz matrices with applications"

Connected through hyperedge HE-2 (induced by source paper "compressive multidimensional harmonic retrieval with prior knowledge"):
  with members:
    - "multi target position and velocity estimation using ofdm communication signals"
    - "adaptive interference removal for uncoordinated radar communication coexistence"
    - "frequency selective vandermonde decomposition of toeplitz matrices with applications"
    - "vandermonde decomposition of multilevel toeplitz matrices with application to multidimensional super resolution"
    - "spectral super resolution with prior knowledge"
    - "exact joint sparse frequency recovery via optimization methods"
    - "atomic norm denoising with applications to line spectral estimation"
    - "compressed sensing off the grid"

Connected through hyperedge HE-3 (induced by source paper "multi target position and velocity estimation using ofdm communication signals"):
  with members:
    - "adaptive interference removal for uncoordinated radar communication coexistence"
    - "complete dictionary recovery over the sphere i overview and the geometric picture"
    - "super resolution of complex exponentials from modulations with unknown waveforms"
    - "direction of arrival estimation using co prime arrays a super resolution viewpoint"
    - "atomic norm denoising with applications to line spectral estimation"
    - "compressed sensing off the grid"
    - "super resolution from noisy data"
    - "towards a mathematical theory of super resolution"

Connected through hyperedge HE-4 (induced by source paper "framework for a perceptive mobile network using joint communication and radar sensing"):
  with members:
    - "toward dual functional radar communication systems optimal waveform design"
    - "mu mimo communications with mimo radar from co existence to joint transmission"
    - "framework for an innovative perceptive mobile network using joint communication and sensing"
    - "energy efficient telemonitoring of physiological signals via compressed sensing a fast algorithm and power consumption evaluation"
    - "compressed sensing off the grid"

Connected through hyperedge HE-5 (induced by source paper "eliminating impulsive noise in pilot aided ofdm channels via dual of penalized atomic norm"):
  with members:
    - "atomic norm denoising with applications to line spectral estimation"
    - "compressed sensing off the grid"
    - "compressive estimation of doubly selective channels in multicarrier systems leakage effects and sparsity enhancing processing"

Connected through hyperedge HE-6 (induced by source paper "atomic norm denoising based joint channel estimation and faulty antenna detection for massive mimo"):
  with members:
    - "spatial dct based channel estimation in multi antenna multi cell interference channels"
    - "off the grid line spectrum denoising and estimation with multiple measurement vectors"
    - "distributed compressive csit estimation and feedback for fdd multi user massive mimo systems"
    - "massive mimo for next generation wireless systems"
    - "on gridless sparse methods for line spectral estimation from complete and incomplete data"
    - "capacity limits and multiplexing gains of mimo channels with transceiver impairments"
    - "scaling up mimo opportunities and challenges with very large arrays"
    - "a coordinated approach to channel estimation in large scale multiple antenna systems"

Connected through hyperedge HE-7 (induced by source paper "millimeter wave beamformed full dimensional mimo channel estimation based on atomic norm minimization"):
  with members:
    - "approximate support recovery of atomic line spectral estimation a tale of resolution and precision"
    - "atomic norm denoising based joint channel estimation and faulty antenna detection for massive mimo"
    - "millimeter wave mimo channel estimation based on adaptive compressed sensing"
    - "non uniform linear antenna array design and optimization for millimeter wave communications"
    - "compressed sensing based multi user millimeter wave systems how many measurements are needed"
    - "vandermonde decomposition of multilevel toeplitz matrices with application to multidimensional super resolution"
    - "exact joint sparse frequency recovery via optimization methods"
    - "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)