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 "reliability of relay networks under random linear network coding"):
  Abstract: We consider a single-source, multiple-relay, single-destination lossy network employing Random Linear Network coding at all transmitting nodes. We address the problem of calculating the probability of successful decoding at the destination node. In contrast with some previous studies, we assume the classical RLNC scheme, in which the relaying nodes simply re-encode packets, without resorting to decoding. In addition, we consider an arbitrary field size and take into account correlation between the relay nodes. We propose a novel upper bound for an arbitrary number of relays, which becomes exact for a single relay. Using Monte Carlo simulations, we show that the proposed bound is very accurate, exhibiting the mean square error as low as $10^{-6}$. We also demonstrate the throughput gain of the proposed scheme over alternative coding and relaying strategies.

Includes members:
  Member "reliability of multicast under random linear network coding":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "operating its g5 dsrc over unlicensed bands a city scale performance evaluation")
  Member "decoding delay performance of random linear network coding for broadcast":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "delay complexity trade off of random linear network coding in wireless broadcast")
  Member "novel performance analysis of network coded communications in single relay networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "reliability of multicast under random linear network coding")
  Member "improved bounds on the decoding failure probability of network coding over multi source multi relay networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "reliability of broadcast communications under sparse random linear network coding")
  Member "performance analysis of random linear network coding in two source single relay networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "reliability of multicast under random linear network coding")
  Member "network coding meets multimedia a review":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "agile data offloading over novel fog computing infrastructure for cavs")
  Member "further results on coding for reliable communication over packet networks":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "reliability of multicast under random linear network coding")
  Member "on coding for reliable communication over packet networks":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "adaptive causal network coding with feedback")

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)