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: "toward energy efficient 5g wireless communications technologies"
  Abstract: The densification and expansion of wireless networks pose new challenges on energy efficiency. With a drastic increase of infrastructure nodes (e.g. ultra-dense deployment of small cells), the total energy consumption may easily exceed an acceptable level. While most studies focus on the energy radiated by the antennas, the bigger part of the total energy budget is actually consumed by the hardware (e.g., coolers and circuit energy consumption). The ability to shutdown infrastructure nodes (or parts of it) or to adapt the transmission strategy according to the traffic will therefore become an important design aspect of future wireless architectures. Network infrastructure should be regarded as a resource that can be occupied or released on demand. However, the modeling and optimization of such systems are complicated by the potential interference coupling between active nodes. In this article, we give an overview on different aspects of this problem. We show how prior knowledge of traffic patterns can be exploited for optimization. Then, we discuss the framework of interference functions, which has proved a useful tool for various types of coupled systems in the literature. Finally, we introduce different classes of algorithms that have the objective of improving the energy efficiency by adapting the network configuration to the traffic load.

Connected through hyperedge HE-1 (induced by source paper "beamforming optimization for physical layer security in miso wireless networks"):
  with members:
    - "mimo beamforming for secure and energy efficient wireless communication"
    - "robust chance constrained optimization for power efficient and secure swipt systems"
    - "secrecy energy efficiency optimization for miso and siso communication networks"
    - "secrecy wireless information and power transfer with miso beamforming"
    - "principles of physical layer security in multiuser wireless networks a survey"
    - "coordinated beamforming for multiuser miso interference channel under rate outage constraints"
    - "spatially selective artificial noise aided transmit optimization for miso multi eves secrecy rate maximization"
    - "outage probability and outage based robust beamforming for mimo interference channels with imperfect channel state information"

Connected through hyperedge HE-2 (induced by source paper "the role of asymptotic functions in network optimization and feasibility studies"):
  with members:
    - "performance limits of solutions to network utility maximization problems"
    - "elementary properties of positive concave mappings with applications to network planning and optimization"
    - "power and load coupling in cellular networks for energy optimization"
    - "joint downlink base station association and power control for max min fairness computation and complexity"
    - "data offloading in load coupled networks a utility maximization framework"
    - "analysis of cell load coupling for lte network planning and optimization"
    - "base station selection for energy efficient network operation with the majorization minimization algorithm"

Connected through hyperedge HE-3 (induced by source paper "power estimation in lte systems with the general framework of standard interference mappings"):
  with members:
    - "power and load coupling in cellular networks for energy optimization"
    - "analysis of cell load coupling for lte network planning and optimization"
    - "base station selection for energy efficient network operation with the majorization minimization algorithm"

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.NI(Networking and Internet Architecture)