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 "caching meets millimeter wave communications for enhanced mobility management in 5g networks"):
  Abstract: One of the most promising approaches to overcome the uncertainty and dynamic channel variations of millimeter wave (mmW) communications is to deploy dual-mode base stations that integrate both mmW and microwave ($\mu$W) frequencies. If properly designed, such dual-mode base stations can enhance mobility and handover in highly mobile wireless environments. In this paper, a novel approach for analyzing and managing mobility in joint $\mu$W-mmW networks is proposed. The proposed approach leverages device-level caching along with the capabilities of dual-mode base stations to minimize handover failures, reduce inter-frequency measurement energy consumption, and provide seamless mobility in emerging dense heterogeneous networks. First, fundamental results on the caching capabilities, including caching probability and cache duration are derived for the proposed dual-mode network scenario. Second, the average achievable rate of caching is derived for mobile users. Third, the proposed cache-enabled mobility management problem is formulated as a dynamic matching game between mobile user equipments (MUEs) and small base stations (SBSs). The goal of this game is to find a distributed handover mechanism that subject to the network constraints on HOFs and limited cache sizes, allows each MUE to choose between executing an HO to a target SBS, being connected to the macrocell base station (MBS), or perform a transparent HO by using the cached content. The formulated matching game allows capturing the dynamics of the mobility management problem caused by HOFs. To solve this dynamic matching problem, a novel algorithm is proposed and its convergence to a two-sided dynamically stable HO policy is proved. Numerical results corroborate the analytical derivations and show that the proposed solution will provides significant reductions in both the HOF and energy consumption by MUEs.

Includes members:
  Member "modeling and analyzing millimeter wave cellular systems":
    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 "mobility management for heterogeneous networks leveraging millimeter wave for seamless handover":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "moth mobility induced outages in thz a beyond 5g b5g application")
  Member "echo state networks for proactive caching in cloud based radio access networks with mobile users":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "a deep learning framework for optimization of miso downlink beamforming")
  Member "caching in the sky proactive deployment of cache enabled unmanned aerial vehicles for optimized quality of experience":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "on the age of information in internet of things systems with correlated devices")
  Member "local multipath model parameters for generating 5g millimeter wave 3gpp like channel impulse response":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "millimeter wave extended nyusim channel model for spatial consistency")
  Member "asymptotic deployment gain a simple approach to characterize the sinr distribution in general cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "smart radio environments empowered by ai reconfigurable meta surfaces an idea whose time has come")
  Member "tractable model for rate in self backhauled millimeter wave cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "joint path selection and rate allocation framework for 5g self backhauled mm wave networks")
  Member "exploiting user mobility for wireless content delivery":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "optimal scheduling of content caching subject to deadline")

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.GT(Computer Science and Game Theory)