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 "on demand deployment of multiple aerial base stations for traffic offloading and network recovery"):
  Abstract: Unmanned aerial vehicles (UAVs) are being utilized for a wide spectrum of applications in wireless networks leading to attractive business opportunities. In the case of abrupt disruption to existing cellular network operation or infrastructure, e.g., due to an unexpected surge in user demand or a natural disaster, UAVs can be deployed to provide instant recovery via temporary wireless coverage in designated areas. A major challenge is to determine efficiently how many UAVs are needed and where to position them in a relatively large 3D search space. To this end, we formulate the problem of 3D deployment of a fleet of UAVs as a mixed integer linear program, and present a greedy approach that mimics the optimal behavior assuming a grid composed of a finite set of possible UAV locations. In addition, we propose and evaluate a novel low complexity algorithm for multiple UAV deployment in a continuous 3D space, based on an unsupervised learning technique that relies on the notion of electrostatics with repulsion and attraction forces. We present performance results for the proposed algorithm as a function of various system parameters and demonstrate its effectiveness compared to the close-to-optimal greedy approach and its superiority compared to recent related work from the literature.

Includes members:
  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-1 (induced by source paper "fundamental rate limits of uav enabled multiple access channel with trajectory optimization")
  Member "efficient 3d aerial base station placement considering users mobility by reinforcement learning":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "voting based multi agent reinforcement learning for intelligent iot")
  Member "placement optimization of uav mounted mobile base stations":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "analysis of uav communications in cell free massive mimo systems")
  Member "coulomb gans provably optimal nash equilibria via potential fields":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "microbatchgan stimulating diversity with multi adversarial discrimination")
  Member "unmanned aerial vehicle with underlaid device to device communications performance and tradeoffs":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "performance analysis of mobile cellular connected drones under practical antenna configurations")
  Member "drone small cells in the clouds design deployment and performance analysis":
    also connected through other hyperedges:
      - Hyperedge HE-6 (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)