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: "phase noise compensation for ofdm systems"
  Abstract: We describe a low-complexity method for time-domain compensation of phase noise in OFDM systems. We extend existing methods in several respects. First, we suggest using the Karhunen–Loeve representation of the phase noise process to estimate the phase noise. We then derive an improved data-directed choice of basis elements for LS phase noise estimation and present its total least square counterpart problem. The proposed method helps overcome one of the major weaknesses of OFDM systems. We also generalize the time-domain phase noise compensation to the multiuser MIMO context. Finally, we present simulation results using both simulated and measured phased noise. We quantify the tracking performance in the presence of residual carrier offset.

Connected through hyperedge HE-1 (induced by source paper "optimal reference signal design for phase noise compensation in multi carrier massive mimo systems"):
  with members:
    - "periodic analog channel estimation aided beamforming for massive mimo systems"
    - "continuous analog channel estimation aided beamforming for massive mimo systems"
    - "on the phase tracking reference signal pt rs design for 5g new radio nr"
    - "hybrid beamforming with selection for multiuser massive mimo systems"
    - "impact of general channel aging conditions on the downlink performance of massive mimo"
    - "hybrid digital and analog beamforming design for large scale antenna arrays"
    - "dynamic subarrays for hybrid precoding in wideband mmwave mimo systems"
    - "hybrid beamforming for massive mimo a survey"

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)