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: "throughput maximization for delay sensitive random access communication"
  Abstract: We consider a single cell uplink in which many devices randomly transmit a data payload to the base station. Given a fixed latency constraint per device, we propose a time and frequency slotted random access scheme with retransmissions, which when necessary, are Chase combined at the receiver. We analyze the proposed setting at constant SNR. We characterize the scaling of random access throughput versus the latency, by optimizing the number of retransmissions and the number of frequency bins. For infinite block length (IBL), we conclude that at low SNR devices should completely share the time and frequency resources. For high SNR, however, the number of frequency bins should scale with altered load, and the slot duration for each retransmission is determined by the outage tolerance. Since infinite packet sizes are not possible, we extend our model to the finite block length (FBL) regime and characterize the gap versus the IBL regime. We also provide some new results for FBL capacity to bound the probability of outage. The proposed random access model gives an upper bound for the total uplink traffic that can be successfully decoded for a single receive antenna given the latency constraint, and provides insights for 5G cellular system design.

Connected through hyperedge HE-1 (induced by source paper "adaptive causal network coding with feedback"):
  with members:
    - "resource allocation and harq optimization for urllc traffic in 5g wireless networks"
    - "tiny codes for guaranteeable delay"
    - "complete mdp convolutional codes"
    - "analysis of feedback error in automatic repeat request"
    - "low delay random linear coding over a stream"
    - "the effect of block wise feedback on the throughput delay trade off in streaming"
    - "an elias bound on the bhattacharyya distance of codes for channels with a zero error capacity"
    - "on the delay advantage of coding in packet erasure networks"

Connected through hyperedge HE-2 (induced by source paper "on error rate analysis for urllc over multiple fading channels"):
  with members:
    - "ultra reliable and low latency wireless communication tail risk and scale"
    - "massive machine type communications in 5g physical and mac layer solutions"
    - "the third order term in the normal approximation for the awgn channel"

Connected through hyperedge HE-3 (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"
    - "arq with cumulative feedback to compensate for burst errors"
    - "complete mdp convolutional codes"
    - "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"

Connected through hyperedge HE-4 (induced by source paper "outage of periodic downlink wireless networks with hard deadlines"):
  with members:
    - "low latency millimeter wave communications traffic dispersion or network densification"
    - "latency and reliability aware task offloading and resource allocation for mobile edge computing"
    - "ultra reliable and low latency communication in mmwave enabled massive mimo networks"
    - "delay performance of wireless communications with imperfect csi and finite length coding"
    - "base station cooperation on the downlink large system analysis"

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)