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: "channel estimation carrier recovery and data detection in the presence of phase noise in ofdm relay systems"
  Abstract: Due to its time-varying nature, oscillator phase noise can significantly degrade the performance of channel estimation, carrier recovery, and data detection blocks in high-speed wireless communication systems. In this paper, we analyze joint channel, \emph{carrier frequency offset (CFO)}, and phase noise estimation plus data detection in \emph{orthogonal frequency division multiplexing (OFDM)} relay systems. To achieve this goal, a detailed transmission framework involving both training and data symbols is presented. In the data transmission phase, a comb-type OFDM symbol consisting of both pilots and data symbols is proposed to track phase noise over an OFDM frame. Next, a novel algorithm that applies the training symbols to jointly estimate the channel responses, CFO, and phase noise based on the maximum a posteriori criterion is proposed. Additionally, a new \emph{hybrid Cram\'{e}r-Rao lower bound} for evaluating the performance of channel estimation and carrier recovery algorithms in OFDM relay networks is derived. Finally, an iterative receiver for joint phase noise estimation and data detection at the destination node is derived. Extensive simulations demonstrate that the application of the proposed estimation and receiver blocks significantly improves the performance of OFDM relay networks in the presence of phase noise.

Connected through hyperedge HE-1 (induced by source paper "phase noise compensation for ofdm systems"):
  with members:
    - "capacity of simo and miso phase noise channels with common separate oscillators"
    - "massive mimo for next generation wireless systems"
    - "channel phase noise and frequency offset in ofdm systems joint estimation data detection and hybrid cramer rao lower bound"
    - "scaling up mimo opportunities and challenges with very large arrays"
    - "understanding the impact of phase noise on active cancellation in wireless full duplex"

Connected through hyperedge HE-2 (induced by source paper "joint data detection and phase noise mitigation for light field video transmission in mimo ofdm systems"):
  with members:
    - "improving bandwidth efficiency in e band communication systems"
    - "cache enabled opportunistic cooperative mimo for video streaming in wireless systems"

Connected through hyperedge HE-3 (induced by source paper "channel phase noise and frequency offset in ofdm systems joint estimation data detection and hybrid cramer rao lower bound"):
  with members:
    - "improving bandwidth efficiency in e band communication 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)