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: "joint altitude beamwidth location and bandwidth optimization for uav enabled communications"
  Abstract: This letter investigates an uplink power control problem for unmanned aerial vehicles (UAVs) assisted wireless communications. We jointly optimize the UAV's flying altitude, antenna beamwidth, UAV's location and ground terminals' allocated bandwidth and transmit power to minimize the sum uplink power subject to the minimal rate demand. An iterative algorithm is proposed with low complexity to obtain a suboptimal solution. Numerical results show that the proposed algorithm can achieve good performance in terms of uplink sum power saving.

Connected through hyperedge HE-1 (induced by source paper "resource allocation for secure multi uav communication systems with multi eavesdropper"):
  with members:
    - "robust trajectory and resource allocation design for secure uav aided communications"
    - "safeguarding wireless network with uavs a physical layer security perspective"
    - "energy efficient resource allocation for secure uav communication systems"
    - "physical layer security in uav systems challenges and opportunities"
    - "cognitive uav communication via joint maneuver and power control"
    - "secrecy energy efficiency maximization for uav enabled mobile relaying"
    - "optimal 3d trajectory design and resource allocation for solar powered uav communication systems"
    - "securing uav communications via joint trajectory and power control"

Connected through hyperedge HE-2 (induced by source paper "mobility assisted over the air computation for backscatter sensor networks"):
  with members:
    - "uav data collection over noma backscatter networks uav altitude and trajectory optimization"
    - "reduced dimension design of mimo over the air computing for data aggregation in clustered iot networks"
    - "ambient backscatter communications a contemporary survey"

Connected through hyperedge HE-3 (induced by source paper "energy efficient resource allocation in uav enabled mobile edge computing networks"):
  with members:
    - "beyond 5g with uavs foundations of a 3d wireless cellular network"
    - "3 d placement of an unmanned aerial vehicle base station for maximum coverage of users with different qos requirements"
    - "liquid state machine learning for resource and cache management in lte u unmanned aerial vehicle uav networks"
    - "uav aided offloading for cellular hotspot"
    - "stochastic optimization and control framework for 5g network slicing with effective isolation"
    - "joint energy minimization and resource allocation in c ran with mobile cloud"
    - "placement optimization of uav mounted mobile base stations"
    - "joint trajectory and communication design for multi uav enabled wireless networks"

Connected through hyperedge HE-4 (induced by source paper "optimized trajectory design in uav based cellular networks for 3d users a double q learning approach"):
  with members:
    - "interference management for cellular connected uavs a deep reinforcement learning approach"
    - "liquid state machine learning for resource and cache management in lte u unmanned aerial vehicle uav networks"
    - "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"
    - "artificial neural networks based machine learning for wireless networks a tutorial"
    - "uav enabled wireless power transfer trajectory design and energy optimization"
    - "caching in the sky proactive deployment of cache enabled unmanned aerial vehicles for optimized quality of experience"
    - "wireless communications with unmanned aerial vehicles opportunities and challenges"

Connected through hyperedge HE-5 (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"
    - "efficient 3d aerial base station placement considering users mobility by reinforcement learning"
    - "placement optimization of uav mounted mobile base stations"
    - "optimal transport theory for cell association in uav enabled cellular networks"
    - "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-6 (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"
    - "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"
    - "power control in uav supported ultra dense networks communications caching and energy transfer"

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)