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: "joint optimization of cloud and edge processing for fog radio access networks"
  Abstract: This work studies the joint design of cloud and edge processing for the downlink of a fog radio access network (F-RAN). In an F-RAN, as in cloud-RAN (C-RAN), a baseband processing unit (BBU) can perform joint baseband processing on behalf of the remote radio heads (RRHs) that are connected to the BBU by means of the fronthaul links. In addition to the minimal functionalities of conventional RRHs in C-RAN, the RRHs in an F-RAN may be equipped with local caches, in which frequently requested contents can be stored, as well as with baseband processing capabilities. They are hence referred to as enhanced RRH (eRRH). This work focuses on the design of the delivery phase for an arbitrary pre-fetching strategy used to populate the caches of the eRRHs. Two fronthauling modes are considered, namely a hard-transfer mode, whereby non-cached files are communicated over the fronthaul links to a subset of eRRHs, and a soft-transfer mode, whereby the fronthaul links are used to convey quantized baseband signals as in a C-RAN. Unlike the hard-transfer mode in which baseband processing is traditionally carried out only at the eRRHs, the soft-transfer mode enables both centralized precoding at the BBU and local precoding at the eRRHs based on the cached contents, by means of a novel superposition coding approach. To attain the advantages of both approaches, a hybrid design of soft- and hard-transfer modes is also proposed. The problem of maximizing the delivery rate is tackled under fronthaul capacity and per-eRRH power constraints. Numerical results are provided to compare the performance of hard- and soft-transfer fronthauling modes, as well as of the hybrid scheme, for different baseline pre-fetching strategies.

Connected through hyperedge HE-1 (induced by source paper "power efficient resource allocation in c rans with sinr constraints and deadlines"):
  with members:
    - "joint energy minimization and resource allocation in c ran with mobile cloud"
    - "base station on off switching in 5g wireless networks approaches and challenges"
    - "recent advances in cloud radio access networks system architectures key techniques and open issues"
    - "energy efficiency of downlink transmission strategies for cloud radio access networks"
    - "inter tier interference suppression in heterogeneous cloud radio access networks"
    - "energy efficient resource assignment and power allocation in heterogeneous cloud radio access networks"
    - "large scale convex optimization for ultra dense cloud ran"
    - "heterogeneous cloud radio access networks a new perspective for enhancing spectral and energy efficiencies"

Connected through hyperedge HE-2 (induced by source paper "spatial soft core caching"):
  with members:
    - "the exact rate memory tradeoff for caching with uncoded prefetching"
    - "spatially correlated content caching for device to device communications"
    - "spatial multi lru caching for wireless networks with coverage overlaps"
    - "adaptive caching networks with optimality guarantees"
    - "optimal geographic caching in cellular networks"
    - "cache aided interference channels"
    - "fundamental limits of caching in wireless d2d networks"
    - "fundamental limits of caching"

Connected through hyperedge HE-3 (induced by source paper "routing based delivery in combination type networks with random topology"):
  with members:
    - "the exact rate memory tradeoff for caching with uncoded prefetching"
    - "coded caching in a multi server system with random topology"
    - "caching in combination networks novel multicast message generation and delivery by leveraging the network topology"
    - "on the optimality of uncoded cache placement"
    - "fundamental limits of caching"
    - "femtocaching wireless video content delivery through distributed caching helpers"

Connected through hyperedge HE-4 (induced by source paper "towards big data processing in iot path planning and resource management of uav base stations in mobile edge computing system"):
  with members:
    - "stochastic joint radio and computational resource management for multi user mobile edge computing systems"
    - "beyond empirical models pattern formation driven placement of uav base stations"
    - "efficient deployment of multiple unmanned aerial vehicles for optimal wireless coverage"
    - "wireless communications with unmanned aerial vehicles opportunities and challenges"
    - "a lyapunov optimization approach for green cellular networks with hybrid energy supplies"

Connected through hyperedge HE-5 (induced by source paper "towards big data processing in iot network management for online edge data processing"):
  with members:
    - "stochastic joint radio and computational resource management for multi user mobile edge computing systems"
    - "beyond empirical models pattern formation driven placement of uav base stations"
    - "a lyapunov optimization approach for green cellular networks with hybrid energy supplies"

Connected through hyperedge HE-6 (induced by source paper "reinforcement learning based resource allocation in fog ran for iot with heterogeneous latency requirements"):
  with members:
    - "optimizing the number of fog nodes for cloud fog thing networks"
    - "resource allocation in noma based fog radio access networks"
    - "a survey on mobile edge networks convergence of computing caching and communications"
    - "recent advances in fog radio access networks performance analysis and radio resource allocation"
    - "recent advances in cloud radio access networks system architectures key techniques and open issues"
    - "learning how to communicate in the internet of things finite resources and heterogeneity"
    - "cluster content caching an energy efficient approach to improve quality of service in cloud radio access networks"
    - "fronthaul constrained cloud radio access networks insights and challenges"

Connected through hyperedge HE-7 (induced by source paper "improved converses and gap results for coded caching"):
  with members:
    - "the exact rate memory tradeoff for caching with uncoded prefetching"
    - "centralized caching and delivery of correlated contents over a gaussian broadcast channel"
    - "benefits of cache assignment on degraded broadcast channels"
    - "cache aided content delivery over erasure broadcast channels"
    - "characterizing the rate memory tradeoff in cache networks within a factor of 2"
    - "physical layer schemes for wireless coded caching"
    - "rate memory trade off for the two user broadcast caching network with correlated sources"
    - "noisy broadcast networks with receiver caching"

Connected through hyperedge HE-8 (induced by source paper "fog aided wireless networks for content delivery fundamental latency tradeoffs"):
  with members:
    - "fundamental tradeoff between storage and latency in cache aided wireless interference networks"
    - "fundamental limits of cache aided interference management"
    - "a learning based approach to caching in heterogenous small cell networks"
    - "fundamental storage latency tradeoff in cache aided mimo interference networks"
    - "fog computing based radio access networks issues and challenges"
    - "a new converse bound for coded caching"
    - "placing dynamic content in caches with small population"
    - "on caching with more users than files"

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.IT(Information Theory)