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 "uav data collection over noma backscatter networks uav altitude and trajectory optimization"):
  Abstract: The recent evolution of ambient backscattering technology has the potential to provide long-range and low-power wireless communications. In this work, we study the unmanned aerial vehicle (UAV)-assisted backscatter networks where the UAV acts both as a mobile power transmitter and as an information collector. We aim to maximize the number of successfully decoded bits in the uplink while minimizing the UAV's flight time by optimizing its altitude. Power-domain NOMA scheme is employed in the uplink. An optimization framework is presented to identify the trade-off between numerous network parameters, such as UAV's altitude, number of backscatter devices, and backscatter coefficients. Numerical results show that an optimal altitude is computable for various network setups and that the impact of backscattering reflection coefficients on the maximum network throughput is significant. Based on this optimal altitude, we also show that an optimal trajectory plan is achievable.

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 "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 "efficient 3d placement of a uav using particle swarm optimization":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "unmanned aerial vehicles uavs a survey on civil applications and key research challenges")
  Member "lora backscatter enabling the vision of ubiquitous connectivity":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "towards flexible wireless charging for medical implants using distributed antenna system")
  Member "backscatter communications for internet of things theory and applications":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "ambient backscatter communications a contemporary survey")
  Member "joint trajectory and communication design for multi uav enabled wireless networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "joint trajectory and resource allocation design for energy efficient secure uav communication systems")
  Member "power domain non orthogonal multiple access noma in 5g systems potentials and challenges":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "mimo noma networks relying on reconfigurable intelligent surface a signal cancellation based design")
  Member "a survey on non orthogonal multiple access for 5g networks research challenges and future trends":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "effective capacity of noma with finite blocklength for low latency communications")

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)