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 broadcast communications under sparse random linear network coding"):
  Abstract: Ultrareliable point-to-multipoint communications are expected to become pivotal in networks offering future dependable services for smart cities. In this regard, sparse random linear network coding techniques have been widely employed to provide an efficient way to improve the reliability of broadcast and multicast data streams. This paper addresses the pressing concern of providing a tight approximation to the probability of a user recovering a data stream protected by this kind of coding technique. In particular, by exploiting the Stein–Chen method, we provide a novel and general performance framework applicable to any combination of system and service parameters, such as finite field sizes, lengths of the data stream, and level of sparsity. The deviation of the proposed approximation from Monte Carlo simulations is negligible, improving significantly on the state-of-the-art performance bounds.

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 "improved bounds on the decoding failure probability of network coding over multi source multi relay networks":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "reliability of relay networks under random linear network coding")
  Member "analysis and optimization of sparse random linear network coding for reliable multicast services":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "on the probability of partial decoding in sparse 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 "network coding meets multimedia a review":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "agile data offloading over novel fog computing infrastructure for cavs")

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)