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 "cache induced hierarchical cooperation in wireless device to device caching networks"):
  Abstract: We consider a wireless device-to-device (D2D) caching network where n nodes are placed on a regular grid of area A(n). Each node caches L_C*F (coded) bits from a library of size L*F bits, where L is the number of files and F is the size of each file. Each node requests a file from the library independently according to a popularity distribution. Under a commonly used "physical model" and Zipf popularity distribution, we characterize the optimal per-node capacity scaling law for extended networks (i.e., A(n). Moreover, we propose a cache-induced hierarchical cooperation scheme and associated cache content placement optimization algorithm to achieve the optimal per-node capacity scaling law. When the path loss exponent \alpha<3, the optimal per-node capacity scaling law achieved by the cache-induced hierarchical cooperation can be significantly better than that achieved by the existing state-of-the-art schemes. To the best of our knowledge, this is the first work that completely characterizes the per-node capacity scaling law for wireless caching networks under the physical model and Zipf distribution with an arbitrary skewness parameter \tau. While scaling law analysis yields clean results, it may not accurately reflect the throughput performance of a large network with a finite number of nodes. Therefore, we also analyze the throughput of the proposed cache-induced hierarchical cooperation for networks of practical size. The analysis and simulations verify that cache-induced hierarchical cooperation can also achieve a large throughput gain over the cache-assisted multihop scheme for networks of practical size.

Includes members:
  Member "the exact rate memory tradeoff for caching with uncoded prefetching":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "fundamental limits of wireless caching under mixed cacheable and uncacheable traffic")
  Member "how much cache is needed to achieve linear capacity scaling in backhaul limited dense wireless networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "edge caching in dense heterogeneous cellular networks with massive mimo aided self backhaul")
  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 "caching in wireless multihop device to device networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "cache placement in two tier hetnets with limited storage capacity cache or buffer")
  Member "on fundamental trade offs of device to device communications in large wireless networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "d2d aware device caching in mmwave cellular networks")
  Member "fundamental limits of cache aided wireless bc interplay of coded caching and csit feedback":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "fundamental limits of wireless caching under mixed cacheable and uncacheable traffic")
  Member "caching and coded multicasting multiple groupcast index coding":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "decentralized asynchronous coded caching design and performance analysis in fog radio access networks")
  Member "hierarchical coded caching":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "subexponential and linear subpacketization coded caching via line graphs and projective geometry")

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)