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: "power control in uav supported ultra dense networks communications caching and energy transfer"
  Abstract: By means of network densification, ultra dense networks (UDNs) can efficiently broaden the network coverage and enhance the system throughput. In parallel, unmanned aerial vehicles (UAVs) communications and networking have attracted increasing attention recently due to their high agility and numerous applications. In this article, we present a vision of UAV-supported UDNs. Firstly, we present four representative scenarios to show the broad applications of UAV-supported UDNs in communications, caching and energy transfer. Then, we highlight the efficient power control in UAV-supported UDNs by discussing the main design considerations and methods in a comprehensive manner. Furthermore, we demonstrate the performance superiority of UAV-supported UDNs via case study simulations, compared to traditional fixed infrastructure based networks. In addition, we discuss the dominating technical challenges and open issues ahead.

Connected through hyperedge HE-1 (induced by source paper "throughput maximization for uav aided backscatter communication networks"):
  with members:
    - "3d trajectory optimization in rician fading for uav enabled data harvesting"
    - "uav aided offloading for cellular hotspot"
    - "securing uav communications via joint trajectory and power control"
    - "spectral and energy efficient wireless powered iot networks noma or tdma"
    - "riding on the primary a new spectrum sharing paradigm for wireless powered iot devices"
    - "joint trajectory and communication design for multi uav enabled wireless networks"
    - "energy efficient data collection in uav enabled wireless sensor network"
    - "uav enabled wireless power transfer trajectory design and energy optimization"

Connected through hyperedge HE-2 (induced by source paper "deep reinforcement learning for unmanned aerial vehicle assisted vehicular networks"):
  with members:
    - "deep reinforcement learning for intelligent transportation systems"
    - "deep reinforcement learning for dynamic multichannel access in wireless networks"
    - "cellular enabled uav communication trajectory optimization under connectivity constraint"
    - "an online ride sharing path planning strategy for public vehicle systems"
    - "joint transportation and charging scheduling in public vehicle systems a game theoretic approach"
    - "sgd learns the conjugate kernel class of the network"
    - "capacity of uav enabled multicast channel joint trajectory design and power allocation"
    - "neural optimizer search with reinforcement learning"

Connected through hyperedge HE-3 (induced by source paper "energy efficient cooperative caching in uav networks"):
  with members:
    - "energy minimization for wireless communication with rotary wing uav"
    - "random caching based cooperative transmission in heterogeneous wireless networks"
    - "joint trajectory and communication design for multi uav enabled wireless networks"
    - "modeling and analysis of cellular networks using stochastic geometry a tutorial"
    - "overcoming endurance issue uav enabled communications with proactive caching"
    - "mitigating interference in content delivery networks by spatial signal alignment the approach of shot noise ratio"
    - "effect of retransmissions on optimal caching in cache enabled small cell networks"
    - "optimization and analysis of probabilistic caching in n tier heterogeneous networks"

Connected through hyperedge HE-4 (induced by source paper "earning maximization with quality of charging service guarantee for iot devices"):
  with members:
    - "fair scheduling in resonant beam charging for iot devices"
    - "wireless charging technologies fundamentals standards and network applications"
    - "wireless charger networking for mobile devices fundamentals standards and applications"
    - "cognitive internet of things a new paradigm beyond connection"
    - "internet of things iot a vision architectural elements and future directions"

Connected through hyperedge HE-5 (induced by source paper "on board deep q network for uav assisted online power transfer and data collection"):
  with members:
    - "joint trajectory and communication design for multi uav enabled wireless networks"
    - "uav assisted cooperative communications with wireless information and power transfer"
    - "uav enabled wireless power transfer trajectory design and energy optimization"
    - "wireless communications with unmanned aerial vehicles opportunities and challenges"

Connected through hyperedge HE-6 (induced by source paper "survey on uav cellular communications practical aspects standardization advancements regulation and security challenges"):
  with members:
    - "understanding uav cellular communications from existing networks to massive mimo"
    - "supporting uav cellular communications through massive mimo"
    - "uav aided offloading for cellular hotspot"
    - "the essential guide to realizing 5g connected uavs with massive mimo"
    - "performance analysis for practical unmanned aerial vehicle networks with los nlos transmissions"
    - "promises and caveats of uplink iot ultra dense networks"
    - "the sky is not the limit lte for unmanned aerial vehicles"
    - "cellular enabled uav communication a connectivity constrained trajectory optimization perspective"

Connected through hyperedge HE-7 (induced by source paper "liquid state machine learning for resource and cache management in lte u unmanned aerial vehicle uav networks"):
  with members:
    - "beyond 5g with uavs foundations of a 3d wireless cellular network"
    - "uav aided offloading for cellular hotspot"
    - "joint altitude beamwidth location and bandwidth optimization for uav enabled communications"
    - "wireless communication using unmanned aerial vehicles uavs optimal transport theory for hover time optimization"
    - "echo state networks for self organizing resource allocation in lte u with uplink downlink decoupling"
    - "joint trajectory and communication design for multi uav enabled wireless networks"
    - "virtual reality over wireless networks quality of service model and learning based resource management"
    - "uav air to ground channel characterization for mmwave systems"

Connected through hyperedge HE-8 (induced by source paper "capacity characterization of uav enabled two user broadcast channel"):
  with members:
    - "the sky is not the limit lte for unmanned aerial vehicles"
    - "placement optimization of uav mounted mobile base stations"
    - "dronecells improving 5g spectral efficiency using drone mounted flying base stations"
    - "joint trajectory and communication design for multi uav enabled wireless networks"
    - "securing uav communications via trajectory optimization"
    - "joint trajectory and communication design for uav enabled multiple access"
    - "uav enabled wireless power transfer trajectory design and energy optimization"
    - "cyclical multiple access in uav aided communications a throughput delay 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.NI(Networking and Internet Architecture)