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: "resource allocation for machine to machine communications with unmanned aerial vehicles"
  Abstract: In this paper, a novel framework for power-efficient, cluster-based machine-to-machine (M2M) communications is proposed. In the studied model, a number of unmanned aerial vehicles (UAVs) are used as aerial base stations to collect data from the cluster heads (CHs) of a set of M2M clusters. To minimize the CHs' transmit power while satisfying the rate requirements of M2M devices, an optimal scheduling and resource allocation mechanism for CH-UAV communications is proposed. First, using the queue rate stability concept, the minimum number of UAVs as well as the dwelling time that each UAV must spend for servicing the CHs are computed. Next, the optimal resource allocation for the CH-UAV communication links is determined such that M2M devices rate requirements are satisfied with a minimum transmit power. Simulation results show that, as the packet transmission probability of machines increases, the minimum number of UAVs required to guarantee the queue rate stability of CHs will also significantly increase. Our results also show that, compared to a case with pre-deployed terrestrial base stations, the average transmit power of CHs will decrease by 68% when UAVs are used.

Connected through hyperedge HE-1 (induced by source paper "utility aware optimal resource allocation protocol for uav assisted small cells with heterogeneous coverage demands"):
  with members:
    - "capacity characterization of uav enabled two user broadcast channel"
    - "3 d placement of an unmanned aerial vehicle base station for maximum coverage of users with different qos requirements"
    - "placement optimization of uav mounted mobile base stations"
    - "joint trajectory and communication design for multi uav enabled wireless networks"
    - "mobile unmanned aerial vehicles uavs for energy efficient internet of things communications"
    - "efficient deployment of multiple unmanned aerial vehicles for optimal wireless coverage"
    - "wireless communications with unmanned aerial vehicles opportunities and challenges"
    - "unmanned aerial vehicle with underlaid device to device communications performance and tradeoffs"

Connected through hyperedge HE-2 (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-3 (induced by source paper "overcoming endurance issue uav enabled communications with proactive caching"):
  with members:
    - "uav aided offloading for cellular hotspot"
    - "energy minimization for wireless communication with rotary wing uav"
    - "common throughput maximization in uav enabled ofdma systems with delay consideration"
    - "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"

Connected through hyperedge HE-4 (induced by source paper "mobile edge computing via a uav mounted cloudlet optimization of bit allocation and path planning"):
  with members:
    - "mobile cloud computing with a uav mounted cloudlet optimal bit allocation for communication and computation"
    - "energy efficient uav communication with trajectory optimization"
    - "parallel and distributed methods for nonconvex optimization part ii applications"
    - "optimal transport theory for power efficient deployment of unmanned aerial vehicles"
    - "wireless communications with unmanned aerial vehicles opportunities and challenges"
    - "unmanned aerial vehicle with underlaid device to device communications performance and tradeoffs"
    - "throughput maximization for mobile relaying systems"
    - "the internet of flying things opportunities and challenges with airborne fog computing and mobile cloud in the clouds"

Connected through hyperedge HE-5 (induced by source paper "mobile cloud computing with a uav mounted cloudlet optimal bit allocation for communication and computation"):
  with members:
    - "placement optimization of uav mounted mobile base stations"
    - "energy efficient uav communication with trajectory optimization"
    - "optimal transport theory for power efficient deployment of unmanned aerial vehicles"
    - "wireless communications with unmanned aerial vehicles opportunities and challenges"
    - "unmanned aerial vehicle with underlaid device to device communications performance and tradeoffs"
    - "mobile internet of things can uavs provide an energy efficient mobile architecture"
    - "throughput maximization for mobile relaying systems"
    - "the internet of flying things opportunities and challenges with airborne fog computing and mobile cloud in the clouds"

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)