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 multicast under random linear network coding"):
  Abstract: We consider a lossy multicast network in which the reliability is provided by means of Random Linear Network Coding. Our goal is to characterise the performance of such network in terms of the probability that a source message is delivered to all destination nodes. Previous studies considered coding over large finite fields, small numbers of destination nodes or specific, often impractical, channel conditions. In contrast, we focus on a general problem, considering arbitrary field size and number of destination nodes, as well as a realistic channel. We propose a lower bound on the probability of successful delivery, which is more accurate than the approximation commonly used in the literature. In addition, we present a novel performance analysis of the systematic version of RLNC. The accuracy of the proposed performance framework is verified via extensive Monte Carlo simulations, where the impact of the network and code parameters are investigated. Specifically, we show that the mean square error of the bound for a ten-user network can be as low as $9 \cdot 10^{-5}$ for non-systematic RLNC.

Includes members:
  Member "reliability of broadcast communications under sparse random linear network coding":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "on the probability of partial decoding in sparse network coding")
  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 relay networks under random linear network coding")
  Member "resource allocation frameworks for network coded layered multimedia multicast services":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "resource allocation for loss tolerant video streaming in embms")
  Member "binary systematic network coding for progressive packet decoding":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "on the probability of partial decoding in sparse network coding")
  Member "optimized network coded scalable video multicasting over embms networks":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "resource allocation for loss tolerant video streaming in embms")
  Member "performance analysis of random linear network coding in two source single relay networks":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "reliability of relay networks under random linear network coding")
  Member "rethinking the intercept probability of random linear network coding":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "secure data offloading strategy for connected and autonomous vehicles")

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)