human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "holistic small cell traffic balancing across licensed and unlicensed bands"
  Abstract: Due to the dramatic growth in mobile data traffic on one hand and the scarcity of the licensed spectrum on the other hand, mobile operators are considering the use of unlicensed bands (especially those in 5 GHz) as complementary spectrum for providing higher system capacity and better user experience. This approach is currently being standardized by 3GPP under the name of LTE Licensed-Assisted Access (LTE-LAA). In this paper, we take a holistic approach for LTE-LAA small cell traffic balancing by jointly optimizing the use of the licensed and unlicensed bands. We pose this traffic balancing as an optimization problem that seeks proportional fair coexistence of WiFi, small cell and macro cell users by adapting the transmission probability of the LTE-LAA small cell in the licensed and unlicensed bands. The motivation for this formulation is for the LTE-LAA small cell to switch between or aggregate licensed and unlicensed bands depending on the interference/traffic level and the number of active users in each band. We derive a closed form solution for this optimization problem and additionally propose a transmission mechanism for the operation of the LTE-LAA small cell on both bands. Through numerical and simulation results, we show that our proposed traffic balancing scheme, besides enabling better LTE-WiFi coexistence and efficient utilization of the radio resources relative to the existing traffic balancing scheme, also provides a better tradeoff between maximizing the total network throughput and achieving fairness among all network flows compared to alternative approaches.

Connected through hyperedge HE-1 (induced by source paper "echo state networks for self organizing resource allocation in lte u with uplink downlink decoupling"):
  with members:
    - "a multi game framework for harmonized lte u and wifi coexistence over unlicensed bands"
    - "opportunistic sleep mode strategies in wireless small cell networks"
    - "learning how to communicate in the internet of things finite resources and heterogeneity"
    - "modeling and analyzing the coexistence of wi fi and lte in unlicensed spectrum"
    - "dynamic clustering and on off strategies for wireless small cell networks"
    - "why to decouple the uplink and downlink in cellular networks and how to do it"
    - "small cell traffic balancing over licensed and unlicensed bands"
    - "joint rate and sinr coverage analysis for decoupled uplink downlink biased cell associations in hetnets"

Connected through hyperedge HE-2 (induced by source paper "proactive resource management for lte in unlicensed spectrum a deep learning perspective"):
  with members:
    - "deep learning for reliable mobile edge analytics in intelligent transportation systems"
    - "echo state networks for self organizing resource allocation in lte u with uplink downlink decoupling"
    - "lstm a search space odyssey"
    - "inter operator resource management for millimeter wave multi hop backhaul networks"
    - "deep learning based dynamic watermarking for secure signal authentication in the internet of things"
    - "coordinated dynamic spectrum management of lte u and wi fi networks"
    - "learning to cooperate via policy search"
    - "long short term memory based recurrent neural network architectures for large vocabulary speech recognition"

Question: Please tell me which class the center node 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)