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 "multi layer gelfand pinsker strategies for the generalized multiple access channel"):
  Abstract: We study a two-user state-dependent generalized multiple-access channel (GMAC) with correlated states. It is assumed that each encoder has \emph{noncausal} access to channel state information (CSI). We develop an achievable rate region by employing rate-splitting, block Markov encoding, Gelfand--Pinsker multicoding, superposition coding and joint typicality decoding. In the proposed scheme, the encoders use a partial decoding strategy to collaborate in the next block, and the receiver uses a backward decoding strategy with joint unique decoding at each stage. Our achievable rate region includes several previously known regions proposed in the literature for different scenarios of multiple-access and relay channels. Then, we consider two Gaussian GMACs with additive interference. In the first model, we assume that the interference is known noncausally at both of the encoders and construct a multi-layer Costa precoding scheme that removes \emph{completely} the effect of the interference. In the second model, we consider a doubly dirty Gaussian GMAC in which each of interferences is known noncausally only at one encoder. We derive an inner bound and analyze the achievable rate region for the latter model and interestingly prove that if one of the encoders knows the full CSI, there exists an achievable rate region which is \emph{independent} of the power of interference.

Includes members:
  Member "multiple access channels with states causally known at transmitters":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "cooperative multiple access channels with distributed state information")
  Member "capacity region of multiple access channel with states known noncausally at one encoder and only strictly causally at the other encoder":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "is non unique decoding necessary")
  Member "capacity bounds for multiuser channels with non causal channel state information at the transmitters":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "broadcasting information subject to state masking over a mimo state dependent gaussian channel")
  Member "multiple access channel with states known noncausally at one encoder and only strictly causally at the other encoder":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "on cooperative multiple access channels with delayed csi at transmitters")
  Member "the state dependent multiple access channel with states available at a cribbing encoder":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "cooperative binning for semideterministic channels")
  Member "multiple access channels with cooperative encoders and channel state information":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "a new and more general capacity theorem for the gaussian channel with two sided input noise dependent state information")
  Member "multiaccess channels with state known to some encoders and independent messages":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "gaussian multiple access via compute and forward")

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)