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: "a two phase power allocation scheme for crns employing noma"
  Abstract: In this paper, we consider the power allocation (PA) problem in cognitive radio networks (CRNs) employing nonorthogonal multiple access (NOMA) technique. Specifically, we aim to maximize the number of admitted secondary users (SUs) and their throughput, without violating the interference tolerance threshold of the primary users (PUs). This problem is divided into a two-phase PA process: a) maximizing the number of admitted SUs; b) maximizing the minimum throughput among the admitted SUs. To address the first phase, we apply a sequential and iterative PA algorithm, which fully exploits the characteristics of the NOMA-based system. Following this, the second phase is shown to be quasiconvex and is optimally solved via the bisection method. Furthermore, we prove the existence of a unique solution for the second phase and propose another PA algorithm, which is also optimal and significantly reduces the complexity in contrast with the bisection method. Simulation results verify the effectiveness of the proposed two-phase PA scheme.

Connected through hyperedge HE-1 (induced by source paper "non orthogonal multiple access noma how it meets 5g and beyond"):
  with members:
    - "securing downlink massive mimo noma networks with artificial noise"
    - "energy efficient joint user rb association and power allocation for uplink hybrid noma oma"
    - "capacity and outage analysis of a dual hop decode and forward relay aided noma scheme"
    - "energy efficient power allocation in uplink mmwave massive mimo with noma"
    - "optimal joint subcarrier and power allocation in noma is strongly np hard"
    - "power domain non orthogonal multiple access noma in 5g systems potentials and challenges"
    - "non orthogonal multiple access in large scale heterogeneous networks"
    - "energy efficient power allocation in millimeter wave massive mimo with non orthogonal multiple access"

Connected through hyperedge HE-2 (induced by source paper "optimum fairness for non orthogonal multiple access"):
  with members:
    - "when mmwave communications meet network densification a scalable interference coordination perspective"
    - "a new noma approach for fair power allocation"
    - "fairness for non orthogonal multiple access in 5g systems"

Connected through hyperedge HE-3 (induced by source paper "a fair individual rate comparison between mimo noma and mimo oma"):
  with members:
    - "noma in 5g systems exciting possibilities for enhancing spectral efficiency"
    - "capacity comparison between mimo noma and mimo oma with multiple users in a cluster"
    - "a general mimo framework for noma downlink and uplink transmission based on signal alignment"
    - "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)