human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "distributed collaborative 3d deployment of uav base stations for on demand coverage"):
  Abstract: Deployment of unmanned aerial vehicles (UAVs) performing as flying aerial base stations (BSs) has a great potential of adaptively serving ground users during temporary events, such as major disasters and massive events. However, planning an efficient, dynamic, and 3D deployment of UAVs in adaptation to dynamically and spatially varying ground users is a highly complicated problem due to the complexity in air-to-ground channels and interference among UAVs. In this paper, we propose a novel distributed 3D deployment method for UAV-BSs in a downlink network for on-demand coverage. Our method consists mainly of the following two parts: sensing-aided crowd density estimation and distributed push-sum algorithm. The first part estimates the ground user density from its observation through on-ground sensors, thereby allowing us to avoid the computationally intensive process of obtaining the positions of all the ground users. On the basis of the estimated user density, in the second part, each UAV dynamically updates its 3D position in collaboration with its neighboring UAVs for maximizing the total coverage. We prove the convergence of our distributed algorithm by employing a distributed push-sum algorithm framework. Simulation results demonstrate that our method can improve the overall coverage with a limited number of ground sensors. We also demonstrate that our method can be applied to a dynamic network in which the density of ground users varies temporally.

Includes members:
  Member "on the number and 3d placement of drone base stations in wireless cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "joint 3d maneuver and power adaptation for secure uav communication with comp reception")
  Member "3 d placement of an unmanned aerial vehicle base station for maximum coverage of users with different qos requirements":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "fundamental rate limits of uav enabled multiple access channel with trajectory optimization")
  Member "a tutorial on uavs for wireless networks applications challenges and open problems":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "performance analysis of mobile cellular connected drones under practical antenna configurations")
  Member "efficient 3d aerial base station placement considering users mobility by reinforcement learning":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "voting based multi agent reinforcement learning for intelligent iot")
  Member "efficient deployment of multiple unmanned aerial vehicles for optimal wireless coverage":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "analysis of uav communications in cell free massive mimo systems")
  Member "the new frontier in ran heterogeneity multi tier drone cells":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "joint 3d maneuver and power adaptation for secure uav communication with comp reception")
  Member "drone small cells in the clouds design deployment and performance analysis":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "coverage analysis of uavs in millimeter wave networks a stochastic geometry approach")

Question: Please tell me which class the source paper 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)