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 "key technologies and system trade offs for detection and localization of amateur drones"):
  Abstract: The use of amateur drones is expected to significantly increase over the upcoming years. However, regulations do not allow such drones to fly over all areas, in addition to typical altitude limitations. As a result, there is an urgent need for amateur drone surveillance solutions. These solutions should include means of accurate detection, classification, and localization of the unwanted drones in a no-fly zone. In this article, we give an overview of promising techniques for modulation classification and signal-strength-based localization of amateur drones by using surveillance drones. By introducing a generic altitude-dependent propagation model, we show how detection and localization performance depend on the altitude of surveillance drones. Particularly, our simulation results show a 25 dB reduction in the minimum detectable power or 10 times coverage enhancement of a surveillance drone by flying at the optimum altitude. Moreover, for a target no-fly zone, the location estimation error of an amateur drone can be remarkably reduced by optimizing the positions of the surveillance drones. Finally, we conclude the article with a general discussion about the future work and possible challenges in aerial surveillance systems.

Includes members:
  Member "electrosense open and big spectrum data":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "a survey on machine learning based performance improvement of wireless networks phy mac and network layer")
  Member "ultra reliable uav communication using altitude and cooperation diversity":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "towards reliable uav swarm communication in d2d enhanced cellular network")
  Member "flight dynamics based recovery of a uav trajectory using ground cameras":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "reconstruction of 3d flight trajectories from ad hoc camera networks")
  Member "deep architectures for modulation recognition":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "a survey on machine learning based performance improvement of wireless networks phy mac and network layer")
  Member "localization in long range ultra narrow band iot networks using rssi":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "localization in ultra narrow band iot networks design guidelines and tradeoffs")
  Member "efficient deployment of multiple unmanned aerial vehicles for optimal wireless coverage":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "analysis of uav communications in cell free massive mimo systems")
  Member "convolutional radio modulation recognition networks":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "a survey on machine learning based performance improvement of wireless networks phy mac and network layer")

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)