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 "heuristic approach for jointly optimizing feicic and uav locations in multi tier lte advanced public safety hetnet"):
  Abstract: UAV enabled communications and networking can enhance wireless connectivity and support emerging services. However, this would require system-level understanding to modify and extend the existing terrestrial network infrastructure. In this paper, we integrate UAVs both as user equipment and base stations into existing LTE-Advanced heterogeneous network (HetNet) and provide system-level insights of this three-tier LTE-Advanced air-ground HetNet (AG-HetNet). This AG-HetNet leverages cell range expansion (CRE), ICIC, 3D beamforming, and enhanced support for UAVs. Using system-level understanding and through brute-force technique and heuristics algorithms, we evaluate the performance of AG-HetNet in terms of fifth percentile spectral efficiency (5pSE) and coverage probability. We compare 5pSE and coverage probability, when aerial base-stations (UABS) are deployed on a fixed hexagonal grid and when their locations are optimized using genetic algorithm (GA) and elitist harmony search algorithm based on genetic algorithm (eHSGA). Our simulation results show the heuristic algorithms outperform the brute-force technique and achieve better peak values of coverage probability and 5pSE. Simulation results also show that trade-off exists between peak values and computation time when using heuristic algorithms. Furthermore, the three-tier hierarchical structuring of FeICIC provides considerably better 5pSE and coverage probability than eICIC.

Includes members:
  Member "predictive deployment of uav base stations in wireless networks machine learning meets contract theory":
    also connected through other hyperedges:
      (none)
  Member "performance analysis for practical unmanned aerial vehicle networks with los nlos transmissions":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "coverage analysis of uavs in millimeter wave networks a stochastic geometry approach")
  Member "interference coordination for aerial and terrestrial nodes in three tier lte advanced hetnet":
    also connected through other hyperedges:
      (none)
  Member "a survey on legacy and emerging technologies for public safety communications":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "unmanned aerial vehicles uavs a survey on civil applications and key research challenges")
  Member "coexistence of terrestrial and aerial users in cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "performance analysis of mobile cellular connected drones under practical antenna configurations")
  Member "a stochastic geometry model of backhaul and user coverage in urban uav networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "coverage analysis of uavs in millimeter wave networks a stochastic geometry approach")
  Member "optimal transport theory for power efficient deployment of unmanned aerial vehicles":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "uav communications for 5g and beyond recent advances and future trends")
  Member "uav assisted heterogeneous networks for capacity enhancement":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "uav communications for 5g and beyond recent advances and future trends")

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)