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: "energy efficient joint user rb association and power allocation for uplink hybrid noma oma"
  Abstract: In this paper, energy efficient resource allocation is considered for an uplink hybrid system, where non-orthogonal multiple access is integrated into orthogonal multiple access (OMA). To ensure the quality of service for the users, a minimum rate requirement is predefined for each user. An energy efficiency (EE) maximization problem is formulated by jointly optimizing the user clustering, channel assignment, and power allocation (PA). To address this problem, a many-to-one bipartite graph is first constructed considering the users and resource blocks (RBs) as the two sets of nodes. Based on swap matching, a joint user-RB association and PA scheme is proposed, which converges within a limited number of iterations. Moreover, for the PA under a given user-RB association, a feasibility condition is first derived. If feasible, a low-complexity algorithm is proposed, which obtains optimal EE for any successive interference cancellation (SIC) order and an arbitrary number of users. In addition, for the special case of two users per cluster, analytical solutions are provided for the two orders in which SIC can be implemented. These solutions shed light on how the power is allocated for each user to maximize the EE. Numerical results are presented, which show that the proposed joint user-RB association and PA algorithm outperforms other hybrid multiple-access-based and OMA-based schemes.

Connected through hyperedge HE-1 (induced by source paper "resource allocation technique for hybrid tdma noma system with opportunistic time assignment"):
  with members:
    - "optimal resource allocation for power efficient mc noma with imperfect channel state information"
    - "power domain non orthogonal multiple access noma in 5g systems potentials and challenges"
    - "resource allocation for downlink noma systems key techniques and open issues"
    - "robust beamforming techniques for non orthogonal multiple access systems with bounded channel uncertainties"
    - "power efficient resource allocation for mc noma with statistical channel state information"
    - "a minorization maximization method for optimizing sum rate in the downlink of non orthogonal multiple access systems"
    - "fairness for non orthogonal multiple access in 5g systems"

Connected through hyperedge HE-2 (induced by source paper "massive access in beyond 5g iot networks with noma np hardness competitiveness and learning"):
  with members:
    - "fast uplink grant for machine type communications challenges and opportunities"
    - "delay constrained input queued switch"
    - "dynamic user clustering and power allocation for uplink and downlink non orthogonal multiple access noma systems"
    - "probabilistic rateless multiple access for machine to machine communication"

Connected through hyperedge HE-3 (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"
    - "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"
    - "a two phase power allocation scheme for crns employing noma"
    - "energy efficient power allocation in millimeter wave massive mimo with non orthogonal multiple access"

Connected through hyperedge HE-4 (induced by source paper "securing downlink massive mimo noma networks with artificial noise"):
  with members:
    - "energy efficient power allocation in uplink mmwave massive mimo with noma"
    - "exploiting inter user interference for secure massive non orthogonal multiple access"
    - "optimal resource allocation for power efficient mc noma with imperfect channel state information"
    - "power domain non orthogonal multiple access noma in 5g systems potentials and challenges"
    - "energy efficient power allocation in millimeter wave massive mimo with non orthogonal multiple access"
    - "resource allocation for downlink noma systems key techniques and open issues"
    - "noma in 5g systems exciting possibilities for enhancing spectral efficiency"
    - "a fair individual rate comparison between mimo noma and mimo oma"

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)