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: "deployment and trajectory optimization for uavs a quantization theory approach"
  Abstract: Optimal deployment and movement of multiple unmanned aerial vehicles (UAVs) is studied. The scenarios of variable data rate with fixed transmission power, and variable transmission power with fixed data rate are considered. First, the optimal deployment of UAVs is studied for the static case of a fixed ground terminal (GT) density. Using high resolution quantization theory, the corresponding best achievable performance (average data rate or transmission power) is determined in the asymptotic regime of a large number of UAVs. Next, the dynamic case where the GT density is allowed to vary periodically through time is considered. For one-dimensional networks, an accurate formula for the total amount of UAV movement that guarantees the best time-averaged performance is determined. In general, the tradeoff between the total UAV movement and the achievable performance is obtained through a Lagrangian approach. A corresponding trajectory optimization algorithm is introduced and shown to guarantee a convergent Lagrangian. Numerical simulations are also carried out to confirm the analytical findings.

Connected through hyperedge HE-1 (induced by source paper "optimal deployments of uavs with directional antennas for a power efficient coverage"):
  with members:
    - "energy efficient resource allocation in uav enabled mobile edge computing networks"
    - "using quantization to deploy heterogeneous nodes in two tier wireless sensor networks"
    - "energy minimization for wireless communication with rotary wing uav"
    - "quantizers with parameterized distortion measures"
    - "reshaping cellular networks for the sky the major factors and feasibility"
    - "backhaul for low altitude uavs in urban environments"
    - "joint altitude and beamwidth optimization for uav enabled multiuser communications"
    - "sensor deployment with limited communication range in homogeneous and heterogeneous wireless sensor networks"

Connected through hyperedge HE-2 (induced by source paper "outage optimized deployment of uavs"):
  with members:
    - "energy efficient resource allocation for secure uav communication systems"
    - "power efficient deployment of uavs as relays"
    - "spatial configuration of agile wireless networks with drone bss and user in the loop"
    - "wireless communication using unmanned aerial vehicles uavs optimal transport theory for hover time optimization"
    - "placement optimization of uav mounted mobile base stations"
    - "providing wireless coverage to high rise buildings using uavs"
    - "cyclical multiple access in uav aided communications a throughput delay tradeoff"
    - "efficient deployment of multiple unmanned aerial vehicles for optimal wireless coverage"

Connected through hyperedge HE-3 (induced by source paper "uav base station location optimization for next generation wireless networks overview and future research directions"):
  with members:
    - "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"
    - "backhaul aware placement of a uav bs with bandwidth allocation for user centric operation and profit maximization"
    - "efficient 3d aerial base station placement considering users mobility by reinforcement learning"
    - "spatial configuration of agile wireless networks with drone bss and user in the loop"
    - "efficient 3d placement of a uav using particle swarm optimization"
    - "placement optimization of uav mounted mobile base stations"
    - "providing wireless coverage to high rise buildings using uavs"

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"
    - "optimal transport theory for cell association in uav enabled cellular networks"
    - "energy efficient 3d uav bs placement versus mobile users density and circuit power"
    - "spectrum sharing and cyclical multiple access in uav aided cellular offloading"

Connected through hyperedge HE-5 (induced by source paper "power efficient deployment of uavs as relays"):
  with members:
    - "placement optimization of uav mounted mobile base stations"
    - "providing wireless coverage to high rise buildings using uavs"
    - "movement efficient sensor deployment in wireless sensor networks"
    - "energy efficient uav communication with trajectory optimization"
    - "optimal transport theory for power efficient deployment of unmanned aerial vehicles"
    - "the new frontier in ran heterogeneity multi tier drone cells"
    - "wireless communications with unmanned aerial vehicles opportunities and challenges"
    - "performance analysis of micro unmanned airborne communication relays for cellular networks"

Connected through hyperedge HE-6 (induced by source paper "quantizers with parameterized distortion measures"):
  with members:
    - "backhaul for low altitude uavs in urban environments"
    - "joint altitude and beamwidth optimization for uav enabled multiuser communications"
    - "sensor deployment with limited communication range in homogeneous and heterogeneous wireless sensor networks"
    - "efficient deployment of multiple unmanned aerial vehicles for optimal wireless coverage"
    - "unmanned aerial vehicle with underlaid device to device communications performance and tradeoffs"

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)