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 "optimizing content caching to maximize the density of successful receptions in device to device networking"):
  Abstract: Device-to-device (   $ \sf {D2D}$   ) communication is a promising approach to optimize the utilization of air interface resources in 5G networks, since it allows decentralized opportunistic short-range communication. For    $ \sf {D2D}$    to be useful, mobile nodes must possess content that other mobiles want. Thus, intelligent caching techniques are essential for    $ \sf {D2D}$   . In this paper, we use results from stochastic geometry to derive the probability of successful content delivery in the presence of interference and noise. We employ a general transmission strategy, where multiple files are cached at the users and different files can be transmitted simultaneously throughout the network. We then formulate an optimization problem, and find the caching distribution that maximizes the density of successful receptions (DSR) under a simple transmission strategy, where a single file is transmitted at a time throughout the network. We model file requests by a Zipf distribution with exponent    $\gamma _{r}$   , which results in an optimal caching distribution that is also a Zipf distribution with exponent    $\gamma _{c}$   , which is related to    $\gamma _{r}$    through a simple expression involving the path loss exponent. We solve the optimal content placement problem for more general demand profiles under Rayleigh, Ricean, and Nakagami small-scale fading distributions. Our results suggest that it is required to flatten the request distribution to optimize the caching performance. We also develop strategies to optimize content caching for the more general case with multiple files, and bound the DSR for that scenario.

Includes members:
  Member "wireless device to device caching networks basic principles and system performance":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "joint optimization of file placement and delivery in cache assisted wireless networks with limited lifetime and cache space")
  Member "caching in wireless multihop device to device networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "cache placement in two tier hetnets with limited storage capacity cache or buffer")
  Member "optimal geographic caching in cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "online convex optimization for caching networks")
  Member "spectrum sharing for device to device communication in cellular networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "sense and predict harnessing spatial interference correlation for cognitive radio networks")
  Member "fundamental limits of caching in wireless d2d networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "fundamental limits of wireless caching under mixed cacheable and uncacheable traffic")
  Member "sinr based k coverage probability in cellular networks with arbitrary shadowing":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "sir meta distribution of k tier downlink heterogeneous cellular networks with cell range expansion")
  Member "base station assisted device to device communications for high throughput wireless video networks":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "degrees of freedom of cache aided wireless cellular networks")
  Member "coding for caches in the plane":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "modeling analysis and optimization of caching in multi antenna small cell networks")

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)