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 "analysis and optimization of sparse random linear network coding for reliable multicast services"):
  Abstract: Point-to-multipoint communications are expected to play a pivotal role in next-generation networks. This paper refers to a cellular system transmitting layered multicast services to a multicast group of users. Reliability of communications is ensured via different random linear network coding (RLNC) techniques. We deal with a fundamental problem: the computational complexity of the RLNC decoder. The higher the number of decoding operations is, the more the user’s computational overhead grows and, consequently, the faster the battery of mobile devices drains. By referring to several sparse RLNC techniques, and without any assumption on the implementation of the RLNC decoder in use, we provide an efficient way to characterize the performance of users targeted by ultra-reliable layered multicast services. The proposed modeling allows to efficiently derive the average number of coded packet transmissions needed to recover one or more service layers. We design a convex resource allocation framework that allows to minimize the complexity of the RLNC decoder by jointly optimizing the transmission parameters and the sparsity of the code. The designed optimization framework also ensures service guarantees to predetermined fractions of users. The performance of the proposed optimization framework is then investigated in a LTE-A eMBMS network multicasting H.264/SVC video services.

Includes members:
  Member "resource allocation frameworks for network coded layered multimedia multicast services":
    also connected through other hyperedges:
      - Hyperedge HE-1 (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-2 (induced by source paper "on the probability of partial decoding in sparse network coding")
  Member "lte enhancements for public safety and security communications to support group multimedia communications":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "uav empowered disaster resilient edge architecture for delay sensitive communication")
  Member "ultra reliable communication in 5g wireless systems":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "ultra reliable communication via optimum power allocation for harq retransmission schemes")
  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")

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)