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: "non orthogonal multiple access for degraded broadcast channels ra cema"
  Abstract: A new non-orthogonal multiple access scheme performing simultaneous transmission to multiple users characterized by different signal-to-noise ratios is proposed. Different users are multiplexed by storing their codewords into a multiplexing matrix according to properly designed patterns and then mapping the columns of the matrix onto the symbols of a higher-order constellation. At the receiver, an interference cancellation algorithm is employed in order to achieve a higher spectral efficiency than orthogonal user multiplexing. Rate-Adaptive Constellation Expansion Multiple Access (RA-CEMA) is an alternative to conventional superposition coding as a solution for transmission on the degraded broadcast channel. It combines the benefits of an increased spectral efficiency with the advantages of reusing the coding and modulation schemes already used in contemporary communication systems, thereby facilitating its adoption in standards.

Connected through hyperedge HE-1 (induced by source paper "short packet downlink transmission with non orthogonal multiple access"):
  with members:
    - "an optimization perspective of the superiority of noma compared to conventional oma"
    - "optimal joint power and subcarrier allocation for full duplex multicarrier non orthogonal multiple access systems"
    - "wirelessly powered communication networks with short packets"
    - "energy efficient packet scheduling with finite blocklength codes convexity analysis and efficient algorithms"
    - "massive machine type communications in 5g physical and mac layer solutions"
    - "enhancing the physical layer security of non orthogonal multiple access in large scale networks"
    - "performance comparison of short length error correcting codes"
    - "a general mimo framework for noma downlink and uplink transmission based on signal alignment"

Connected through hyperedge HE-2 (induced by source paper "noma principles and recent results"):
  with members:
    - "noma based random access with multichannel aloha"
    - "design of massive mimo noma with limited feedback"
    - "a minorization maximization method for optimizing sum rate in the downlink of non orthogonal multiple access systems"
    - "the application of mimo to non orthogonal multiple access"
    - "fairness for non orthogonal multiple access in 5g systems"
    - "on the performance of non orthogonal multiple access in 5g systems with randomly deployed users"

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)