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 "time asynchronous gaussian multiple access relay channel with correlated sources"):
  Abstract: We study the transmission of a set of correlated sources $(U_1,\cdots,U_K)$ over a Gaussian multiple access relay channel with time asynchronism between the encoders. We assume that the maximum possible offset ${\mathsf{d_{max}}}(n)$ between the transmitters grows without bound as the block length $n \rightarrow \infty$ while the relative ratio ${{\mathsf{d_{max}}}(n) / n}$ of the maximum possible offset to the block length asymptotically vanishes. For such a joint source-channel coding problem, and under specific gain conditions, we derive necessary and sufficient conditions for reliable communications and show that separate source and channel coding achieves optimal performance. In particular, we first derive a general outer bound on the source entropy content for all channel gains as our main result. Then, using Slepian-Wolf source coding combined with the channel coding scheme introduced in \cite{Cover_McEliece:81} on top of block Markov coding, we show that the thus achieved inner bound matches the outer bound. Consequently, as a corollary, we also address the problem of sending a pair of correlated sources over a two user interference channel in the same context.

Includes members:
  Member "asynchronous transmission over single user state dependent channels":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "on the multiple access channel with asynchronous cognition")
  Member "on joint source channel coding for correlated sources over multiple access relay channels":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "communicating correlated sources over an interference channel")
  Member "source channel coding theorems for the multiple access relay channel":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "the secrecy capacity of gaussian mimo channels with finite memory full version")
  Member "optimality and approximate optimality of source channel separation in networks":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "a new approach to lossy network compression of a tuple of correlated multivariate gaussian rvs")
  Member "communication under strong asynchronism":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "on the reliability function of distributed hypothesis testing under optimal detection")

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)