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 "constant delay and constant feedback moving window network coding for wireless multicast design and asymptotic analysis"):
  Abstract: A major challenge of wireless multicast is to be able to support a large number of users while simultaneously maintaining low delay and low feedback overhead. In this paper, we develop a joint coding and feedback scheme named Moving Window Network Coding with Anonymous Feedback (MWNC-AF) that successfully addresses this challenge. In particular, we show that our scheme simultaneously achieves both a constant decoding delay and a constant feedback overhead, irrespective of the number of receivers $n$, without sacrificing either throughput or reliability. We explicitly characterize the asymptotic decay rate of the tail of the delay distribution, and prove that transmitting a fixed amount of information bits into the MWNC-AF encoder buffer in each time-slot (called "constant data injection process") achieves the fastest decay rate, thus showing how to obtain delay optimality in a large deviation sense. We then investigate the average decoding delay of MWNC-AF, and show that when the traffic load approaches the capacity, the average decoding delay under the constant injection process is at most one half of that under a Bernoulli injection process. In addition, we prove that the per-packet encoding and decoding complexity of MWNC-AF both scale as $O(\log n)$, with the number of receivers $n$. Our simulations further underscore the performance of our scheme through comparisons with other schemes and show that the delay, encoding and decoding complexity are low even for a large number of receivers, demonstrating the efficiency, scalability, and ease of implementability of MWNC-AF.

Includes members:
  Member "scheduling of multicast and unicast services under limited feedback by using rateless codes":
    also connected through other hyperedges:
      (none)
  Member "network control without csi using rateless codes for downlink cellular systems":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "scheduling of multicast and unicast services under limited feedback by using rateless codes")
  Member "the effect of block wise feedback on the throughput delay trade off in streaming":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "adaptive causal network coding with feedback")
  Member "throughput of rateless codes over broadcast erasure channels":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "high throughput low delay wireless multicast via multi channel moving window codes")
  Member "dynamic rate adaptation for improved throughput and delay in wireless network coded broadcast":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "high throughput low delay wireless multicast via multi channel moving window codes")
  Member "three schemes for wireless coded broadcast to heterogeneous users":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "wireless device to device caching networks basic principles and system performance")
  Member "throughput delay analysis of random linear network coding for wireless broadcasting":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "delay complexity trade off of random linear network coding in wireless broadcast")
  Member "network coding meets tcp":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "mds coding is better than replication for job completion times")

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)