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: "dynamic cross layer beamforming in hybrid powered communication systems with harvest use trade strategy"
  Abstract: The application of renewable energy is a promising solution to realize the Green Communications. However, if the cellular systems are solely powered by the renewable energy, the weather dependence of the renewable energy arrival makes the systems unstable. On the other hand, the proliferation of the smart grid facilitates the loads with two-way energy trading capability. Hence, a hybrid powered cellular system, which combines the smart grid with the base stations, can reduce the grid energy expenditure and improve the utilization efficiency of the renewable energy. In this paper, the long-term grid energy expenditure minimization problem is formulated as a stochastic optimization model. By leveraging the stochastic optimization theory, we reformulate the stochastic optimization problem as a \mbox{per-frame} grid energy plus weighted penalized packet rate minimization problem, which is NP-hard. As a result, two suboptimal algorithms, which jointly consider the effects of the channel quality and the packet reception failure, are proposed based on the successive approximation beamforming (SABF) technique and the \mbox{zero-forcing} beamforming (ZFBF) technique. The convergence properties of the proposed suboptimal algorithms are established, and the corresponding computational complexities are analyzed. Simulation results show that the proposed SABF algorithm outperforms the ZFBF algorithm in both grid energy expenditure and packet delay. By tuning a control parameter, the grid energy expenditure can be traded for the packet delay under the proposed stochastic optimization model.

Connected through hyperedge HE-1 (induced by source paper "cross layer scheduling and beamforming in smart grid powered cellular networks with heterogeneous energy coordination"):
  with members:
    - "deep reinforcement learning for adaptive caching in hierarchical content delivery networks"
    - "optimal 3d trajectory design and resource allocation for solar powered uav communication systems"
    - "robust energy efficient beamforming in misome swipt systems with proportional secrecy rate"
    - "a hybrid energy sharing framework for green cellular networks"
    - "an overview of sustainable green 5g networks"
    - "ergodic energy management leveraging resource variability in distribution grids"
    - "comp meets smart grid a new communication and energy cooperation paradigm"
    - "power delay tradeoff with predictive scheduling in integrated cellular and wi fi networks"

Connected through hyperedge HE-2 (induced by source paper "cross layer scheduling and beamforming in smart grid powered small cell networks"):
  with members:
    - "robust energy efficient beamforming in misome swipt systems with proportional secrecy rate"
    - "a hybrid energy sharing framework for green cellular networks"
    - "an overview of sustainable green 5g networks"
    - "power delay tradeoff with predictive scheduling in integrated cellular and wi fi networks"
    - "a general utility optimization framework for energy harvesting based wireless communications"
    - "transmit power minimization in small cell networks under time average qos constraints"

Connected through hyperedge HE-3 (induced by source paper "robust energy efficient beamforming in misome swipt systems with proportional secrecy rate"):
  with members:
    - "robust secrecy energy efficient beamforming in misome swipt systems with proportional fairness"
    - "rf based energy harvesting in decode and forward relaying systems ergodic and outage capacities"
    - "secure beamforming in full duplex swipt systems with loopback self interference cancellation"
    - "large scale multiantenna multisine wireless power transfer"
    - "joint optimization of power and data transfer in multiuser mimo systems"
    - "robust resource allocation for mimo wireless powered communication networks based on a non linear eh model"
    - "network densification in 5g from the short range communications perspective"
    - "wireless information and power transfer nonlinearity waveform design and rate energy tradeoff"

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)