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: "joint power control and beamforming for uplink non orthogonal multiple access in 5g millimeter wave communications"
  Abstract: In this paper, we investigate the combination of two key enabling technologies for the fifth generation (5G) wireless mobile communication, namely millimeter-wave (mmWave) communications and non-orthogonal multiple access (NOMA). In particular, we consider a typical 2-user uplink mmWave-NOMA system, where the base station (BS) equips an analog beamforming structure with a single RF chain and serves 2 NOMA users. An optimization problem is formulated to maximize the achievable sum rate of the 2 users while ensuring a minimal rate constraint for each user. The problem turns to be a joint power control and beamforming problem, i.e., we need to find the beamforming vectors to steer to the two users simultaneously subject to an analog beamforming structure, and meanwhile control appropriate power on them. As direct search for the optimal solution of the non-convex problem is too complicated, we propose to decompose the original problem into two sub-problems that are relatively easy to solve: one is a power control and beam gain allocation problem, and the other is an analog beamforming problem under a constant-modulus constraint. The rational of the proposed solution is verified by extensive simulations, and the performance evaluation results show that the proposed sub-optimal solution achieve a close-to-bound uplink sum-rate performance.

Connected through hyperedge HE-1 (induced by source paper "deep reinforcement learning for 5g networks joint beamforming power control and interference coordination"):
  with members:
    - "a deep learning framework for optimization of miso downlink beamforming"
    - "deep learning for tdd and fdd massive mimo mapping channels in space and frequency"
    - "a framework for automated cellular network tuning with reinforcement learning"
    - "deep learning in downlink coordinated multipoint in new radio heterogeneous networks"
    - "q learning algorithm for volte closed loop power control in indoor small cells"
    - "partially blind handovers for mmwave new radio aided by sub 6 ghz lte signaling"
    - "deep learning coordinated beamforming for highly mobile millimeter wave systems"
    - "deep reinforcement learning for dynamic multichannel access in wireless networks"

Connected through hyperedge HE-2 (induced by source paper "a survey of rate optimal power domain noma schemes for enabling technologies of future wireless networks"):
  with members:
    - "generalized coordinated multipoint gcomp enabled noma outage capacity and power allocation"
    - "what role can noma play in massive mimo"
    - "uav data collection over noma backscatter networks uav altitude and trajectory optimization"
    - "uav communications for 5g and beyond recent advances and future trends"
    - "when full duplex wireless meets non orthogonal multiple access opportunities and challenges"
    - "on optimizing vlc networks for downlink multi user transmission a survey"
    - "beam design and user scheduling for nonorthogonal multiple access with multiple antennas based on pareto optimality"
    - "spatial modulation assisted multi antenna non orthogonal multiple access"

Connected through hyperedge HE-3 (induced by source paper "clustered millimeter wave networks with non orthogonal multiple access"):
  with members:
    - "cache enabled hetnets with millimeter wave small cells"
    - "user association and resource allocation in unified noma enabled heterogeneous ultra dense networks"
    - "exploiting multiple access in clustered millimeter wave networks noma or oma"
    - "modeling and analysis of d2d millimeter wave networks with poisson cluster processes"
    - "optimal user scheduling and power allocation for millimeter wave noma systems"
    - "modeling and analyzing millimeter wave cellular systems"
    - "coverage analysis for millimeter wave networks the impact of directional antenna arrays"
    - "non orthogonal multiple access in large scale heterogeneous networks"

Connected through hyperedge HE-4 (induced by source paper "energy efficient joint user rb association and power allocation for uplink hybrid noma oma"):
  with members:
    - "energy efficient power allocation in uplink mmwave massive mimo with noma"
    - "energy efficient noma enabled heterogeneous cloud radio access networks"
    - "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"
    - "capacity comparison between mimo noma and mimo oma with multiple users in a cluster"

Connected through hyperedge HE-5 (induced by source paper "energy efficient power allocation in uplink mmwave massive mimo with noma"):
  with members:
    - "spectrum and energy efficient beamspace mimo noma for millimeter wave communications using lens antenna array"
    - "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"
    - "capacity comparison between mimo noma and mimo oma with multiple users in a cluster"
    - "an overview of signal processing techniques for millimeter wave mimo systems"
    - "spatially sparse precoding in millimeter wave mimo systems"

Connected through hyperedge HE-6 (induced by source paper "user fairness non orthogonal multiple access noma for 5g millimeter wave communications with analog beamforming"):
  with members:
    - "optimal user scheduling and power allocation for millimeter wave noma systems"
    - "joint power allocation and beamforming for non orthogonal multiple access noma in 5g millimeter wave communications"
    - "a survey on non orthogonal multiple access for 5g networks research challenges and future trends"
    - "hierarchical codebook design for beamforming training in millimeter wave communication"
    - "codebook design for millimeter wave channel estimation with hybrid precoding structure"
    - "on the number of rf chains and phase shifters and scheduling design with hybrid analog digital beamforming"
    - "fairness for non orthogonal multiple access in 5g systems"
    - "channel estimation and hybrid precoding for millimeter wave cellular systems"

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)