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: "message passing based joint cfo and channel estimation in millimeter wave systems with one bit adcs"
  Abstract: Channel estimation at millimeter wave (mmWave) is challenging when large antenna arrays are used. Prior work has leveraged the sparse nature of mmWave channels via compressed sensing based algorithms for channel estimation. Most of these algorithms, though, assume perfect synchronization and are vulnerable to phase errors that arise due to carrier frequency offset (CFO) and phase noise. Recently sparsity-aware, non-coherent beamforming algorithms that are robust to phase errors were proposed for narrowband phased array systems with full resolution analog-to-digital converters (ADCs). Such energy based algorithms, however, are not robust to heavy quantization at the receiver. In this paper, we develop a joint CFO and wideband channel estimation algorithm that is scalable across different mmWave architectures. Our method exploits the sparsity of mmWave MIMO channel in the angle-delay domain, in addition to compressibility of the phase error vector. We formulate the joint estimation as a sparse bilinear optimization problem and then use message passing for recovery. We also give an efficient implementation of a generalized bilinear message passing algorithm for the joint estimation in mmWave systems with one-bit ADCs. Simulation results show that our method is able to recover the CFO and the channel compressively, even in the presence of phase noise.

Connected through hyperedge HE-1 (induced by source paper "a two stage approach to estimate cfo and channel with one bit adcs"):
  with members:
    - "on low resolution adcs in practical 5g millimeter wave massive mimo systems"
    - "newtonized orthogonal matching pursuit for line spectrum estimation with multiple measurement vectors"
    - "channel estimation and performance analysis of one bit massive mimo systems"
    - "millimeter wave channel estimation via exploiting joint sparse and low rank structures"
    - "newtonized orthogonal matching pursuit frequency estimation over the continuum"
    - "an overview of signal processing techniques for millimeter wave mimo systems"
    - "channel estimation in broadband millimeter wave mimo systems with few bit adcs"
    - "millimeter wave cellular wireless networks potentials and challenges"

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)