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 "gaussian multiple and random access in the finite blocklength regime"):
  Abstract: This paper presents finite-blocklength achievability bounds for the Gaussian multiple access channel (MAC) and random access channel (RAC) under average-error and maximal-power constraints. Using random codewords uniformly distributed on a sphere and a maximum likelihood decoder, the derived MAC bound on each transmitter's rate matches the MolavianJazi-Laneman bound (2015) in its first- and second-order terms, improving the remaining terms to $\frac{1}{2}\frac{\log n}{n}+O(\frac1n)$ bits per channel use. The result then extends to a RAC model in which neither the encoders nor the decoder knows which of $K$ possible transmitters are active. In the proposed rateless coding strategy, decoding occurs at a time $n_t$ that depends on the decoder's estimate $t$ of the number of active transmitters $k$. Single-bit feedback from the decoder to all encoders at each potential decoding time $n_i$, $i \leq t$, informs the encoders when to stop transmitting. For this RAC model, the proposed code achieves the same first-, second-, and third-order performance as the best known result for the Gaussian MAC in operation.

Includes members:
  Member "fundamental limits of many user mac with finite payloads and fading":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "massive access for future wireless communication systems")
  Member "lossless source coding in the point to point multiple access and random access scenarios":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "fundamental limits of lossless data compression with side information")
  Member "random access channel coding in the finite blocklength regime":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "massive access for future wireless communication systems")
  Member "capacity of gaussian many access channels":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "unsourced multiuser sparse regression codes achieve the symmetric mac capacity")
  Member "a proof of the strong converse theorem for gaussian multiple access channels":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "exponential strong converse for successive refinement with causal decoder side information")
  Member "the third order term in the normal approximation for the awgn channel":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "optimal resource allocation in ground wireless networks supporting unmanned aerial vehicle transmissions")
  Member "many access channels the gaussian case with random user activities":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "on the fundamental limits of mimo massive access communication")
  Member "on the dispersions of three network information theory problems":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "lossless source coding in the point to point multiple access and random access scenarios")

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)