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 "distributed user association in energy harvesting dense small cell networks a mean field multi armed bandit approach"):
  Abstract: The emerging ultra-dense small cell networks (UD-SCNs) will need to combat a variety of challenges. On the one hand, massive number of devices sharing the limited wireless resources renders centralized control mechanisms infeasible due to the excessive cost of information acquisition and computation. On the other hand, to reduce the energy consumption from fixed power grid and/or battery, network entities (e.g., small cell base stations and user devices) may need to rely on the energy harvested from the ambient environment (e.g., from environmental sources). However, opportunistic energy harvesting introduces uncertainty in the network operation. In this paper, we study the distributed user association problem for energy harvesting UD-SCNs. After reviewing the state-of-the-art research, we outline the major challenges that arise in the presence of energy harvesting due to the uncertainty (e.g., limited knowledge on energy harvesting process or channel profile) as well as limited computational capacities. Finally, we propose an approach based on the mean-field multi-armed bandit games to solve the uplink user association problem for energy harvesting devices in a UD-SCN in the presence of uncertainty.

Includes members:
  Member "distributed wireless power transfer with energy feedback":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "wirelessly powered sensor networks power allocation for channel estimation and energy beamforming")
  Member "distributed user association in energy harvesting small cell networks an exchange economy with uncertainty":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "energy efficient resource allocation in machine to machine communications with multiple access and energy harvesting for iot")
  Member "distributed user association in energy harvesting small cell networks a probabilistic bandit model":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "energy efficient optimization of wireless powered 5g full duplex cellular networks a mean field game approach")
  Member "multi armed bandits with application to 5g small cells":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "thirty years of machine learning the road to pareto optimal next generation wireless networks")
  Member "user association in 5g networks a survey and an outlook":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "a tutorial on beam management for 3gpp nr at mmwave frequencies")
  Member "optimum transmission policies for energy harvesting sensor networks powered by a mobile control center":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "minimum throughput maximization in uav aided wireless powered communication networks")
  Member "sum rate maximizing cell association via dual connectivity":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "exploiting dual connectivity in heterogeneous cellular networks")
  Member "multicast aware caching for small cell networks":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "a survey on mobile edge networks convergence of computing caching and 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)