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: "orthogonal precoding for ultra reliable wireless communication links"
  Abstract: All diversity sources of a wireless communication channel must be utilized to enable ultra-reliable wireless communication links. Hadani et al. propose the two dimensional discrete symplectic Fourier transform (DSFT) as orthogonal pre-coder for orthogonal frequency division multiplexing (OFDM) in time- and frequency-selective channels. In this paper we investigate general orthogonal precoding (OP) and develop a low-complexity iterative channel estimation and (near) maximum likelihood detection algorithm using soft-symbol feedback. We present a general but compact framework to analyze the performance of OP and its ability to utilize time- and frequency-diversity. We are able to proof that all constant modulus sequences, e.g. such as the DSFT or Walsh-Hadamard sequences, lead to the same performance for OP. Our OP receiver is tested by numerical link level simulation for the DSFT, two dimensional discrete prolate spheroidal sequences, and Walsh-Hadamard sequences. We demonstrate that our receiver achieves a gain of about $4.8\,\text{dB}$ for a bit error rate of $10^{-4}$ compared to OFDM for a relative velocity of $0\ldots200\,\text{km/h}$ for the exemplary use-case of a vehicle-to-vehicle communication link.

Connected through hyperedge HE-1 (induced by source paper "orthogonal time frequency space modulation"):
  with members:
    - "on otfs modulation for high doppler fading channels"
    - "a simple two stage equalizer with simplified orthogonal time frequency space modulation over rapidly time varying channels"
    - "low complexity equalization for orthogonal time and frequency signaling otfs"
    - "analysis of discrete time mimo ofdm based orthogonal time frequency space modulation"
    - "low complexity modem structure for ofdm based orthogonal time frequency space modulation"
    - "otfs orthogonal time frequency space"
    - "comparison of the achievable rates in ofdm and single carrier modulation with i i d inputs"
    - "what will 5g be"

Connected through hyperedge HE-2 (induced by source paper "embedded pilot aided channel estimation for otfs in delay doppler channels"):
  with members:
    - "orthogonal time frequency space modulation"
    - "otfs a new generation of modulation addressing the challenges of 5g"
    - "interference cancellation and iterative detection for orthogonal time frequency space modulation"
    - "low complexity equalization for orthogonal time and frequency signaling otfs"
    - "analysis of discrete time mimo ofdm based orthogonal time frequency space modulation"
    - "low complexity modem structure for ofdm based orthogonal time frequency space modulation"

Connected through hyperedge HE-3 (induced by source paper "roast rapid orthogonal approximate slepian transform"):
  with members:
    - "approximating sampled sinusoids and multiband signals using multiband modulated dpss dictionaries"
    - "compressive sensing of analog signals using discrete prolate spheroidal sequences"

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)