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: "mobility support for cellular connected unmanned aerial vehicles performance and analysis"
  Abstract: Beyond visual line-of-sight connectivity is key for use cases of unmanned aerial vehicles (UAVs) such as package delivery, infrastructure inspection, and rescue missions. Cellular networks stand ready to support flying UAVs by providing wide-area, quality, and secure connectivity for UAV operations. Ensuring reliable connections in the presence of UAV movements is important for safety control and operations of UAVs. With increasing height above the ground, the radio environment changes. Using terrestrial cellular networks to provide connectivity to the UAVs moving in the sky may face new challenges. In this article, we share some of our findings in mobility support for cellular connected UAVs. We first identify how the radio environment changes with altitude and analyze the corresponding implications on mobility performance. We then present evaluation results to shed light on the mobility performance of cellular connected UAVs. We also discuss potential enhancements for improving mobility performance in the sky.

Connected through hyperedge HE-1 (induced by source paper "performance analysis of mobile cellular connected drones under practical antenna configurations"):
  with members:
    - "optimizing joint probabilistic caching and channel access for clustered d2d networks"
    - "3gpp inspired stochastic geometry based mobility model for a drone cellular network"
    - "detecting sybil attacks using proofs of work and location in vanets"
    - "privacy preserving smart parking system using blockchain and private information retrieval"
    - "b ride ride sharing with privacy preservation trust and fair payment atop public blockchain"
    - "on the reliability of wireless virtual reality at terahertz thz frequencies"
    - "privacy preserving and collusion resistant charging coordination schemes for smart grid"
    - "a vision of 6g wireless systems applications trends technologies and open research problems"

Connected through hyperedge HE-2 (induced by source paper "mobility in the sky performance and mobility analysis for cellular connected uavs"):
  with members:
    - "capacity and coverage enhancement using long endurance tethered airborne base stations"
    - "trajectory design for cellular connected uav under outage duration constraint"
    - "interference management for cellular connected uavs a deep reinforcement learning approach"
    - "a vision of 6g wireless systems applications trends technologies and open research problems"
    - "cellular connectivity for uavs network modeling performance analysis and design guidelines"
    - "on the 3 d placement of airborne base stations using tethered uavs"
    - "trajectory optimization for cellular connected uav under outage duration constraint"
    - "drones in distress a game theoretic countermeasure for protecting uavs against gps spoofing"

Connected through hyperedge HE-3 (induced by source paper "efficient drone mobility support using reinforcement learning"):
  with members:
    - "5g handover using reinforcement learning"
    - "machine learning for reliable mmwave systems blockage prediction and proactive handoff"
    - "the sky is not the limit lte for unmanned aerial vehicles"
    - "a telecom perspective on the internet of drones from lte advanced to 5g"
    - "a tutorial on uavs for wireless networks applications challenges and open problems"
    - "survey on uav cellular communications practical aspects standardization advancements regulation and security challenges"

Connected through hyperedge HE-4 (induced by source paper "machine learning for wireless connectivity and security of cellular connected uavs"):
  with members:
    - "interference management for cellular connected uavs a deep reinforcement learning approach"
    - "securing uav communications via joint trajectory and power control"
    - "deep learning for signal authentication and security in massive internet of things systems"
    - "a tutorial on uavs for wireless networks applications challenges and open problems"
    - "a comprehensive study of deep bidirectional lstm rnns for acoustic modeling in speech recognition"
    - "proactive resource management for lte in unlicensed spectrum a deep learning perspective"
    - "job selection in a network of autonomous uavs for delivery of goods"
    - "caching in the sky proactive deployment of cache enabled unmanned aerial vehicles for optimized quality of experience"

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)