human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "precoded chebyshev nlms based pre distorter for nonlinear led compensation in noma vlc"):
  Abstract: Visible light communication (VLC) is one of the main technologies driving the future 5G communication systems due to its ability to support high data rates with low power consumption, thereby facilitating high speed green communications. To further increase the capacity of VLC systems, a technique called non-orthogonal multiple access (NOMA) has been suggested to cater to increasing demand for bandwidth, whereby users' signals are superimposed prior to transmission and detected at each user equipment using successive interference cancellation (SIC). Some recent results on NOMA exist which greatly enhance the achievable capacity as compared to orthogonal multiple access techniques. However, one of the performance-limiting factors affecting VLC systems is the nonlinear characteristics of a light emitting diode (LED). This paper considers the nonlinear LED characteristics in the design of pre-distorter for cognitive radio inspired NOMA in VLC, and proposes singular value decomposition based Chebyshev precoding to improve performance of nonlinear multiple-input multiple output NOMA-VLC. A novel and generalized power allocation strategy is also derived in this work, which is valid even in scenarios when users experience similar channels. Additionally, in this work, analytical upper bounds for the bit error rate of the proposed detector are derived for square $M$-quadrature amplitude modulation.

Includes members:
  Member "non orthogonal multiple access for visible light communications":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "optical rate splitting multiple access for visible light communications")
  Member "a minorization maximization method for optimizing sum rate in the downlink of non orthogonal multiple access systems":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "resource allocation technique for hybrid tdma noma system with opportunistic time assignment")
  Member "non orthogonal multiple access noma for downlink multiuser mimo systems user clustering beamforming and power allocation":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "optical rate splitting multiple access for visible light communications")
  Member "the application of mimo to non orthogonal multiple access":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "mimo noma networks relying on reconfigurable intelligent surface a signal cancellation based design")
  Member "a general mimo framework for noma downlink and uplink transmission based on signal alignment":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "mimo noma networks relying on reconfigurable intelligent surface a signal cancellation based design")
  Member "application of non orthogonal multiple access in lte and 5g networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "a survey on the security and the evolution of osmotic and catalytic computing for 5g networks")
  Member "a general framework for transmission with transceiver distortion and some applications":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "sensitivity analysis for binary sampling systems via quantitative fisher information lower bounds")

Question: Please tell me which class the source paper 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)