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 small cell networks a probabilistic bandit model"):
  Abstract: We investigate a distributed downlink user association problem in a dynamic small cell network, where every small base station (SBS) obtains its required energy through ambient energy harvesting. On the one hand, energy harvesting is inherently opportunistic, so that the amount of available energy is a random variable. On the other hand, users arrive at random and require different wireless services, rendering the energy consumption a random variable. In this paper, we develop a probabilistic framework to mathematically model and analyze the random behavior of energy harvesting and energy consumption. We further analyze the probability of QoS satisfaction (success probability), for each user with respect to every SBS. The proposed user association scheme is distributed in the sense that every user independently selects its corresponding SBS with the success probability serving as the performance metric. The success probability however depends on a variety of random factors such as energy harvesting, channel quality, and network traffic, whose distribution or statistical characteristics might not be known at users. Since acquiring the knowledge of these random variables (even statistical) is very costly in a dense network, we develop a bandit-theoretical formulation for distributed SBS selection when no prior information is available at users. The performance is analyzed both theoretically and numerically.

Includes members:
  Member "multi armed bandits with application to 5g small cells":
    also connected through other hyperedges:
      - Hyperedge HE-1 (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-2 (induced by source paper "a tutorial on beam management for 3gpp nr at mmwave frequencies")
  Member "multi access communications with energy harvesting a multi armed bandit model and the optimality of the myopic policy":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "distributed power control for large energy harvesting networks a multi agent deep reinforcement learning approach")
  Member "cooperative interference mitigation and handover management for heterogeneous cloud small cell networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "an edge computing empowered radio access network with uav mounted fso fronthaul and backhaul key challenges and approaches")
  Member "optimizing user association and spectrum allocation in hetnets a utility perspective":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "resource allocation in green dense cellular networks complexity and algorithms")
  Member "channel selection for network assisted d2d communication via no regret bandit learning with calibrated forecasting":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "multi armed bandits for decentralized ap selection in enterprise wlans")
  Member "a context aware matching game for user association in wireless small cell networks":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "distributed user association in energy harvesting small cell networks an exchange economy with uncertainty")
  Member "matching theory for priority based cell association in the downlink of wireless small cell networks":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "early acceptance matching game for user association in 5g cellular hetnet")

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)