human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "arq with cumulative feedback to compensate for burst errors"
  Abstract: We propose a cumulative feedback-based ARQ (CF ARQ) protocol for a sliding window of size 2 over packet erasure channels with unreliable feedback. We exploit a matrix signal-flow graph approach to analyze probability-generating functions of transmission and delay times. Contrasting its performance with that of the uncoded baseline scheme for ARQ, developed by Ausavapattanakun and Nosratinia, we demonstrate that CF ARQ can provide significantly less average delay under bursty feedback, and gains up to about 20% in terms of throughput. We also outline the benefits of CF ARQ under burst errors and asymmetric channel conditions. The protocol is more predictable across statistics, hence is more stable. This can help design robust systems when feedback is unreliable. This feature may be preferable for meeting the strict end-to-end latency and reliability requirements of future use cases of ultra-reliable low-latency communications in 5G, such as mission-critical communications and industrial control for critical control messaging.

Connected through hyperedge HE-1 (induced by source paper "tiny codes for guaranteeable delay"):
  with members:
    - "resource allocation and harq optimization for urllc traffic in 5g wireless networks"
    - "ultra reliable and low latency wireless communication tail risk and scale"
    - "the sky is not the limit lte for unmanned aerial vehicles"
    - "complete mdp convolutional codes"
    - "throughput maximization for delay sensitive random access communication"
    - "analysis of feedback error in automatic repeat request"
    - "low delay random linear coding over a stream"
    - "wide area wireless communication challenges for the internet of things"

Question: Please tell me which class the center node 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)