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 base station location optimization for next generation wireless networks overview and future research directions"):
  Abstract: Unmanned aerial vehicles mounted base stations (UAV-BSs) are expected to become one of the significant components of the Next Generation Wireless Networks (NGWNs). Rapid deployment, mobility, higher chances of unobstructed propagation path, and flexibility features of UAV-BSs have attracted significant attention. Despite, potentially, high gains brought by UAV-BSs in NGWNs, many challenges are also introduced by them. Optimal location assignment to UAV-BSs, arguably, is the most widely investigated problem in the literature on UAV-BSs in NGWNs. This paper presents a comprehensive survey of the literature on the location optimization of UAV-BSs in NGWNs. A generic optimization framework through a universal Mixed Integer Non-Linear Programming (MINLP) formulation is constructed and the specifications of its constituents are elaborated. The generic problem is classified into a novel taxonomy. Due to the highly challenging nature of the optimization problem a range of solutions are adopted in the literature which are also covered under the aforementioned classification. Furthermore, future research directions on UAV-BS location optimization in 5G and beyond non-terrestrial aerial communication systems are discussed.

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 "backhaul aware placement of a uav bs with bandwidth allocation for user centric operation and profit maximization":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "on the 3 d placement of airborne base stations using tethered uavs")
  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 "spatial configuration of agile wireless networks with drone bss and user in the loop":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "backhaul aware optimization of uav base station location and bandwidth allocation for profit maximization")
  Member "efficient 3d placement of a uav using particle swarm optimization":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "unmanned aerial vehicles uavs a survey on civil applications and key research challenges")
  Member "placement optimization of uav mounted mobile base stations":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "analysis of uav communications in cell free massive mimo systems")
  Member "providing wireless coverage to high rise buildings using uavs":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "unmanned aerial vehicles uavs a survey on civil applications and key research challenges")

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)