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 "mismatched multi letter successive decoding for the multiple access channel"):
  Abstract: This paper studies channel coding for the discrete memoryless multiple-access channel with a given (possibly suboptimal) decoding rule. A multi-letter successive decoding rule depending on an arbitrary non-negative decoding metric is considered, and achievable rate regions and error exponents are derived both for the standard MAC (independent codebooks), and for the cognitive MAC (one user knows both messages) with superposition coding. In the cognitive case, the rate region and error exponent are shown to be tight with respect to the ensemble average. The rate regions are compared with those of the commonly-considered decoder that chooses the message pair maximizing the decoding metric, and numerical examples are given for which successive decoding yields a strictly higher sum rate for a given pair of input distributions.

Includes members:
  Member "random coding error exponents for the two user interference channel":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "exact error and erasure exponents for the asymmetric broadcast channel")
  Member "re proving channel polarization theorems an extremality and robustness analysis":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "channel polarization through the lens of blackwell measures")
  Member "polarization as a novel architecture to boost the classical mismatched capacity of b dmcs":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "channel capacity of polar coding with a given polar mismatched successive cancellation decoder")
  Member "a technique for deriving one shot achievability results in network information theory":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "exponential strong converse for successive refinement with causal decoder side information")
  Member "multiuser coding techniques for mismatched decoding":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "on the reliability function of the discrete memoryless relay channel")
  Member "mismatched decoding error exponents second order rates and saddlepoint approximations":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "saddlepoint approximations for short packet wireless communications")
  Member "a general formula for the mismatch capacity":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "strategic communication with side information at the decoder")
  Member "on achievable rates for channels with mismatched decoding":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "mismatched decoding error exponents second order rates and saddlepoint approximations")

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)