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 "capacity and coverage enhancement using long endurance tethered airborne base stations"):
  Abstract: Airborne base stations (carried by drones) have a great potential to enhance coverage and capacity of cellular networks. Multiple scenarios and use cases will highly benefit from such technology such as (i) offloading terrestrial base stations (BSs) in dense and urban areas, and (ii) providing coverage for rural areas. However, one of the main challenges facing the deployment of airborne BSs is the limited available energy at the drone, which limits the flight time. In fact, most of the currently used unmanned aerial vehicles (UAVs) can only operate for one hour maximum. This limits the performance of the UAV-enabled cellular network due to the need to frequently visit the ground station to recharge, leaving the UAV's coverage area temporarily out of service. In this article, we propose a new UAV-enabled cellular network setup based on tethered UAVs (TUAVs). In the proposed setup, the TUAV is connected to a ground station (GS) through a tether, which provides the TUAV with both energy and data. This enables a flight that can stay for days. We describe in detail the components of the proposed system. Furthermore, we enlist the main advantages of a TUAV-enabled cellular network compared to typical untethered UAVs. Next, we discuss the potential applications and use cases for TUAVs. Finally, we discuss the challenges, design considerations, and future research directions to realize the proposed setup.

Includes members:
  Member "backhaul aware placement of a uav bs with bandwidth allocation for user centric operation and profit maximization":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "on the 3 d placement of airborne base stations using tethered uavs")
  Member "a tutorial on uavs for wireless networks applications challenges and open problems":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "performance analysis of mobile cellular connected drones under practical antenna configurations")
  Member "backhaul for low altitude uavs in urban environments":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "coverage analysis of uavs in millimeter wave networks a stochastic geometry approach")
  Member "joint trajectory and communication design for multi uav enabled wireless networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "joint trajectory and resource allocation design for energy efficient secure uav communication systems")
  Member "energy efficient uav communication with trajectory optimization":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "joint trajectory and resource allocation design for energy efficient secure uav communication systems")
  Member "fso based vertical backhaul fronthaul framework for 5g wireless networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "cellular traffic offloading through tethered uav deployment and user association")

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.IT(Information Theory)