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: "use of non orthogonal multiple access in dual hop relaying"
  Abstract: To improve the sum-rate (SR) of the dual-hop relay system, a novel two-stage power allocation scheme with non-orthogonal multiple access (NOMA) is proposed. In this scheme, after the reception of the superposition coded symbol with a power allocation from the source, the relay node forwards a new superposition coded symbol with another power allocation to the destination. By employing the maximum ratio combination (MRC), the destination jointly decodes the information symbols from the source and the relay. Assuming Rayleigh fading channels, closed-form solution of the ergodic SR at high signal-to-noise ratio (SNR) is derived and a practical power allocation is also designed for the proposed NOMA scheme. Through numerical results, it is shown that the performance of the proposed scheme is significantly improved compared with the existing work.

Connected through hyperedge HE-1 (induced by source paper "non orthogonal multiple access for 5g and beyond"):
  with members:
    - "downlink non orthogonal multiple access with limited feedback"
    - "optimal user scheduling and power allocation for millimeter wave noma systems"
    - "coordinated multi point comp transmission in downlink multi cell noma systems models and spectral efficiency performance"
    - "low complexity receiver for multi level polar coded modulation in non orthogonal multiple access"
    - "massive non orthogonal multiple access for cellular iot potentials and limitations"
    - "power domain non orthogonal multiple access noma in 5g systems potentials and challenges"
    - "modulation and multiple access for 5g networks"
    - "robust beamforming techniques for non orthogonal multiple access systems with bounded channel uncertainties"

Connected through hyperedge HE-2 (induced by source paper "modulation and multiple access for 5g networks"):
  with members:
    - "power domain non orthogonal multiple access noma in 5g systems potentials and challenges"
    - "non orthogonal multiple access in large scale heterogeneous networks"
    - "capacity comparison between mimo noma and mimo oma with multiple users in a cluster"
    - "wireless powered communications with non orthogonal multiple access"
    - "nonorthogonal multiple access in large scale underlay cognitive radio networks"
    - "design of massive mimo noma with limited feedback"
    - "optimal joint power and subcarrier allocation for mc noma systems"
    - "relay selection for cooperative noma"

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)