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 "delay performance of wireless communications with imperfect csi and finite length coding"):
  Abstract: With the rise of critical machine-to-machine applications, next generation wireless communication systems must be designed with strict constraints on the latency and reliability. A key question in this context relates to channel state estimation, which allows the transmitter to adapt the code rate to the channel. In this work, we characterize the trade-off between the estimation sequence length and data codeword length: shorter channel estimation leaves more time for the actual payload transmission but reduces the estimation accuracy and causes more decoding errors. Using lower coding rates can mitigate this effect, but may result in a higher backlog of data at the transmitter. We analyze this trade-off using queueing analysis on top of accurate models of the physical layer, which also account for the finite blocklength of the channel code. Based on a novel closed-form approximation for the error probability given the rate, we show that finding the optimal rate adaptation strategy becomes a convex problem. The optimal rate adaptation strategy and the optimal training sequence length, which both depend on the latency and reliability constraints of the application, can improve the delay performance by an order of magnitude, compared to suboptimal strategies that do not consider those constraints.

Includes members:
  Member "on the delay performance of interference channels":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "delay violation probability and age of information interplay in the two user multiple access channel")
  Member "green communication via type i arq finite block length analysis":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "ultra reliable communication via optimum power allocation for harq retransmission schemes")
  Member "finite block length analysis of the incremental redundancy harq":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "physical layer security in the finite blocklength regime over fading channels")
  Member "quasi static simo fading channels at finite blocklength":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "joint power control and rate allocation enabling ultra reliability and energy efficiency in simo wireless networks")
  Member "throughput of cognitive radio systems with finite blocklength codes":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "noma enhanced terrestrial and aerial iot networks with partial csi")
  Member "diversity versus channel knowledge at finite block length":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "on single antenna rayleigh block fading channels at finite blocklength")
  Member "multiuser mimo achievable rates with downlink training and channel state feedback":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "beyond dirty paper coding for multi antenna broadcast channel with partial csit a rate splitting approach")

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)