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 "a satisfactory power control for 5g self organizing networks"):
  Abstract: SmallCells are deployed in order to enhance the network performance by bringing the network closer to the user. However, as the number of low power nodes grows increasingly, the overall energy consumption of the SmallCells base stations cannot be ignored. A relevant amount of energy could be saved through several techniques, especially power control mechanisms. In this paper, we are concerned with energy aware self organizing networks that guarantee a satisfactory performance. We consider satisfaction equilibria, mainly the efficient satisfaction equilibrium (ESE), to ensure a target quality of service (QoS) and save energy. First, we identify conditions of existence and uniqueness of ESE under a stationary channel assumption. We fully characterize the ESE and prove that, whenever it exists, it is a solution of a linear system. Moreover, we define satisfactory Pareto optimality and show that, at the ESE, no player can increase its QoS without degrading the overall performance. Under a fast fading channel assumption, as the robust satisfaction equilibrium solution is very restrictive, we propose an alternative solution namely the long term satisfaction equilibrium, and describe how to reach this solution efficiently. Finally, in order to find satisfactory solution per all users, we propose fully distributed strategic learning schemes based on Banach-Picard, Mann and Bush Mosteller algorithms, and show through simulations their qualitative properties. fully distributed strategic learning schemes based on Banach Picard, Mann and Bush Mosteller algorithms, and show through simulations their qualitative properties.

Includes members:
  Member "ultra dense small cell networks turning density into energy efficiency":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "wireless edge computing with latency and reliability guarantees")
  Member "uav assisted heterogeneous networks for capacity enhancement":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "heuristic approach for jointly optimizing feicic and uav locations in multi tier lte advanced public safety hetnet")
  Member "transmit power minimization in small cell networks under time average qos constraints":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "cross layer scheduling and beamforming in smart grid powered cellular networks with heterogeneous energy coordination")
  Member "what will 5g be":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "5g network slicing using sdn and nfv a survey of taxonomy architectures and future challenges")
  Member "quality of service provisioning in decentralized networks a satisfaction equilibrium approach":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "joint path selection and rate allocation framework for 5g self backhauled mm wave networks")

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)