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: "optimal transport theory for cell association in uav enabled cellular networks"
  Abstract: In this paper, a novel framework for delay-optimal cell association in unmanned aerial vehicle (UAV)-enabled cellular networks is proposed. In particular, to minimize the average network delay under any arbitrary spatial distribution of the ground users, the optimal cell partitions of UAVs and terrestrial base stations (BSs) are determined. To this end, using the powerful mathematical tools of optimal transport theory, the existence of the solution to the optimal cell association problem is proved and the solution space is completely characterized. The analytical and simulation results show that the proposed approach yields substantial improvements of the average network delay.

Connected through hyperedge HE-1 (induced by source paper "q learning based aerial base station placement for fairness enhancement in mobile networks"):
  with members:
    - "on the number and 3d placement of drone base stations in wireless cellular networks"
    - "joint altitude beamwidth location and bandwidth optimization for uav enabled communications"
    - "efficient 3d aerial base station placement considering users mobility by reinforcement learning"
    - "placement optimization of uav mounted mobile base stations"
    - "coexistence of terrestrial and aerial users in cellular networks"
    - "backhaul aware robust 3d drone placement in 5g wireless networks"
    - "wireless communications with unmanned aerial vehicles opportunities and challenges"
    - "a quantitative measure of fairness and discrimination for resource allocation in shared computer systems"

Connected through hyperedge HE-2 (induced by source paper "cellular enabled uav communication a connectivity constrained trajectory optimization perspective"):
  with members:
    - "interference management for cellular connected uavs a deep reinforcement learning approach"
    - "beyond 5g with uavs foundations of a 3d wireless cellular network"
    - "comp in the sky uav placement and movement optimization for multi user communications"
    - "capacity characterization of uav enabled two user broadcast channel"
    - "on the number and 3d placement of drone base stations in wireless cellular networks"
    - "3 d placement of an unmanned aerial vehicle base station for maximum coverage of users with different qos requirements"
    - "uav aided offloading for cellular hotspot"
    - "energy minimization for wireless communication with rotary wing uav"

Connected through hyperedge HE-3 (induced by source paper "beyond 5g with uavs foundations of a 3d wireless cellular network"):
  with members:
    - "interference management for cellular connected uavs a deep reinforcement learning approach"
    - "on the number and 3d placement of drone base stations in wireless cellular networks"
    - "3 d placement of an unmanned aerial vehicle base station for maximum coverage of users with different qos requirements"
    - "uav aided offloading for cellular hotspot"
    - "a tutorial on uavs for wireless networks applications challenges and open problems"
    - "uav enabled aerial base station bs iii iii capacity characterization of uav enabled two user broadcast channel"
    - "common throughput maximization in uav enabled ofdma systems with delay consideration"
    - "wireless communication using unmanned aerial vehicles uavs optimal transport theory for hover time optimization"

Connected through hyperedge HE-4 (induced by source paper "spatial configuration of agile wireless networks with drone bss and user in the loop"):
  with members:
    - "on the number and 3d placement of drone base stations in wireless cellular networks"
    - "configurations and diagnosis for ultra dense heterogeneous networks from empirical measurements to technical solutions"
    - "dynamic base station repositioning to improve performance of drone small cells"
    - "placement optimization of uav mounted mobile base stations"
    - "user association and bandwidth allocation for terrestrial and aerial base stations with backhaul considerations"
    - "energy efficient 3d uav bs placement versus mobile users density and circuit power"
    - "deployment and trajectory optimization for uavs a quantization theory approach"
    - "spectrum sharing and cyclical multiple access in uav aided cellular offloading"

Connected through hyperedge HE-5 (induced by source paper "downlink analysis in unmanned aerial vehicle uav assisted cellular networks with clustered users"):
  with members:
    - "uplink coverage performance of an underlay drone cell for temporary events"
    - "3gpp inspired hetnet model using poisson cluster process sum product functionals and downlink coverage"
    - "uplink performance analysis in d2d enabled mmwave cellular networks with clustered users"
    - "modeling and analysis of cellular networks using stochastic geometry a tutorial"
    - "coverage maximization for a poisson field of drone cells"
    - "coverage in downlink heterogeneous mmwave cellular networks with user centric small cell deployment"
    - "efficient deployment of multiple unmanned aerial vehicles for optimal wireless coverage"
    - "enriched k tier hetnet model to enable the analysis of user centric small cell deployments"

Connected through hyperedge HE-6 (induced by source paper "collaborative artificial intelligence ai for user cell association in ultra dense cellular systems"):
  with members:
    - "an introduction to deep learning for the physical layer"
    - "echo state networks for self organizing resource allocation in lte u with uplink downlink decoupling"
    - "cognitive hierarchy theory for distributed resource allocation in the internet of things"
    - "artificial neural networks based machine learning for wireless networks a tutorial"
    - "distributed user association in energy harvesting dense small cell networks a mean field multi armed bandit approach"
    - "downlink and uplink cell association with traditional macrocells and millimeter wave small cells"
    - "caching in the sky proactive deployment of cache enabled unmanned aerial vehicles for optimized quality of experience"
    - "learning how to communicate in the internet of things finite resources and heterogeneity"

Connected through hyperedge HE-7 (induced by source paper "energy minimization for wireless communication with rotary wing uav"):
  with members:
    - "ultra reliable uav communication using altitude and cooperation diversity"
    - "placement optimization of uav mounted mobile base stations"
    - "joint trajectory and communication design for multi uav enabled wireless networks"
    - "energy efficient data collection in uav enabled wireless sensor network"
    - "joint altitude and beamwidth optimization for uav enabled multiuser communications"
    - "cyclical multiple access in uav aided communications a throughput delay tradeoff"
    - "efficient deployment of multiple unmanned aerial vehicles for optimal wireless coverage"
    - "designing and implementing future aerial communication networks"

Connected through hyperedge HE-8 (induced by source paper "small cell association with networked flying platforms novel algorithms and performance bounds"):
  with members:
    - "on the number and 3d placement of drone base stations in wireless cellular networks"
    - "wireless communication using unmanned aerial vehicles uavs optimal transport theory for hover time optimization"
    - "user association and bandwidth allocation for terrestrial and aerial base stations with backhaul considerations"
    - "a novel airborne self organising architecture for 5g networks"
    - "backhaul aware robust 3d drone placement in 5g wireless networks"
    - "efficient deployment of multiple unmanned aerial vehicles for optimal wireless coverage"
    - "fso based vertical backhaul fronthaul framework for 5g wireless networks"
    - "drone small cells in the clouds design deployment and performance analysis"

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)