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 "random linear network coding for wireless layered video broadcast general design methods for adaptive feedback free transmission"):
  Abstract: This paper studies the problem of broadcasting layered video streams over heterogeneous single-hop wireless networks using feedback-free random linear network coding (RLNC). We combine RLNC with unequal error protection (UEP) and our main purpose is twofold. First, to systematically investigate the benefits of UEP+RLNC layered approach in servicing users with different reception capabilities. Second, to study the effect of not using feedback, by comparing feedback-free schemes with idealistic full-feedback schemes. To these ends, we study `expected percentage of decoded frames' as a key content-independent performance metric and propose a general framework for calculation of this metric, which can highlight the effect of key system, video and channel parameters. We study the effect of number of layers and propose a scheme that selects the optimum number of layers adaptively to achieve the highest performance. Assessing the proposed schemes with real H.264 test streams, the trade-offs among the users' performances are discussed and the gain of adaptive selection of number of layers to improve the trade-offs is shown. Furthermore, it is observed that the performance gap between the proposed feedback-free scheme and the idealistic scheme is very small and the adaptive selection of number of video layers further closes the gap.

Includes members:
  Member "analysis and optimization of sparse random linear network coding for reliable multicast services":
    also connected through other hyperedges:
      - Hyperedge HE-1 (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-2 (induced by source paper "resource allocation for loss tolerant video streaming in embms")
  Member "adaptive prioritized random linear coding and scheduling for layered data delivery from multiple servers":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "a rolling horizon dynamic programming approach for collaborative caching")
  Member "inter session network coding for transmitting multiple layered streams over single hop wireless networks":
    also connected through other hyperedges:
      (none)
  Member "joint optimization of throughput and packet drop rate for delay sensitive applications in tdd satellite network coded systems":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "inter session network coding for transmitting multiple layered streams over single hop wireless networks")
  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")
  Member "effective delay control in online network coding":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "reliability of multicast under random linear network coding")
  Member "a quantitative measure of fairness and discrimination for resource allocation in shared computer systems":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "coexistence mechanism between embb and urllc in 5g wireless 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)