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 "fundamental limits on delivery time in cloud and cache aided heterogeneous networks"):
  Abstract: A Fog radio access network is considered as a network architecture candidate to meet the soaring demand in terms of reliability, spectral efficiency, and latency in next generation wireless networks. This architecture combines the benefits associated with centralized cloud processing and wireless edge caching enabling primarily low-latency transmission under moderate fronthaul capacity requirements. The F-RAN we consider in this paper is composed of a centralized cloud server which is connected through fronthaul links to two edge nodes serving two mobile users through a Z-shaped partially connected wireless network. We define an information-theoretic metric, the delivery time per bit (DTB), that captures the worst-case per-bit delivery latency for conveying any requested content to the users. For the cases when cloud and wireless transmission occur either sequentially or in parallel, we establish coinciding lower and upper bounds on the DTB as a function of cache size, backhaul capacity and wireless channel parameters. Through optimized rate allocation, our achievability scheme determines the best combination of private, common signalling and interference neutralization that matches the converse. Our converse bounds use subsets of wireless, fronthaul and caching resources of the F-RAN as side information that enable a single receiver to decode either one or both users' requested files. We show the optimality on the DTB for all channel regimes. In case of serial transmission, the functional DTB-behavior changes at fronthaul capacity thresholds. In this context, we combine multiple channel regimes to classes of channel regimes which share the same fronthaul capacity thresholds and as such the same DTB-functional. In total, our analysis identifies four classes; in only three of those edge caching and cloud processing can provide nontrivial synergestic and non-synergestic performance gains.

Includes members:
  Member "fundamental tradeoff between storage and latency in cache aided wireless interference networks":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "fundamental limits of wireless caching under mixed cacheable and uncacheable traffic")
  Member "degrees of freedom of cache aided wireless interference networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "fundamental limits of wireless caching under mixed cacheable and uncacheable traffic")
  Member "fundamental limits of cache aided interference management":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "the exact rate memory tradeoff for caching with uncoded prefetching")
  Member "coded caching for a large number of users":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "an index coding approach to caching with uncoded cache placement")
  Member "fog computing based radio access networks issues and challenges":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "mode selection and resource allocation in sliced fog radio access networks a reinforcement learning approach")
  Member "joint optimization of cloud and edge processing for fog radio access networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "power efficient resource allocation in c rans with sinr constraints and deadlines")
  Member "backhaul traffic balancing and dynamic content centric clustering for the downlink of fog radio access network":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "a comprehensive survey on fog computing state of the art and research challenges")
  Member "content centric sparse multicast beamforming for cache enabled cloud ran":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "joint optimization of file placement and delivery in cache assisted wireless networks with limited lifetime and cache space")

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)