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 "on channels with asynchronous side information"):
  Abstract: Several channels with asynchronous side information are introduced. We first consider channels that are state dependent with asynchronous side information at the transmitter. It is assumed that the state information sequence is a possibly delayed version of the state sequence, and that the encoder and the decoder are aware of the fact that the state information might be delayed. It is additionally assumed that an upper bound on the delay is known to both encoder and decoder, but other than that, they are ignorant of the actual delay. We consider both the causal and the noncausal cases and present achievable rates for these channels, and the corresponding coding schemes. We find the capacity of the asynchronous Gel'fand-Pinsker channel with feedback. We further consider a memoryless state dependent channel with asynchronous side information at both the transmitter and receiver, and establish a single-letter expression for its capacity. Finally, we introduce the asynchronous cognitive multiple-access channel with an uninformed encoder, and an informed one. We assume that the informed encoder knows in advance the message of the uninformed encoder. We present a multi-letter expression for the capacity region of this channel, and state single-letter outer and inner bounds on its capacity region. Finally, we study the binary as well as the Gaussian asynchronous multiple-access channels with an uninformed encoder.

Includes members:
  Member "an achievability scheme for the compound channel with state noncausally available at the encoder":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "on the capacity of the carbon copy onto dirty paper channel")
  Member "on the capacity of compound state dependent channels with states known at the transmitter":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "on the capacity of the carbon copy onto dirty paper channel")
  Member "coding for the feedback gel fand pinsker channel and the feedforward wyner ziv source":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "fundamental limits of communication over state dependent channels with feedback")
  Member "carbon copying onto dirty paper":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "on the capacity of the carbon copy onto dirty paper channel")

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)