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 "a mismatched joint source channel coding perspective of probabilistic amplitude shaping achievable rates and error exponents"):
  Abstract: Probabilistic Amplitude Shaping (PAS) is a novel method of reliable commmunication over channels with non-uniform capacity achieving input distribution. The encoder of PAS is a concatenation of a distribution matcher with systematic encoding of a Forward Error Correction (FEC) code whereas the PAS decoder is a concatenation of a mismatched FEC decoder and dematcher. In recent works PAS has been shown to close the shaping gap to Shannon capacity for discrete input AWGN channel for a wide range of SNR values. In this paper we modify the classical joint source-channel coding setup to include the salient features of PAS and we derive the Gallager style error exponent and consequently achievable rates for this setup.

Includes members:
  Member "achievable rates for probabilistic shaping":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "achievable information rates for probabilistic amplitude shaping a minimum randomness approach via random sign coding arguments")
  Member "comparison of geometric and probabilistic shaping with application to atsc 3 0":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "introducing enumerative sphere shaping for optical communication systems with short blocklengths")
  Member "optimal quantization for distribution synthesis":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "a note on reverse pinsker inequalities")
  Member "on probabilistic shaping of quadrature amplitude modulation for the nonlinear fiber channel":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "analysis and optimization of tail biting spatially coupled protograph ldpc codes for bicm id systems")
  Member "constant composition distribution matching":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "rate constrained shaping codes for structured sources")

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)