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 "protograph based ldpc code design for bit metric decoding"):
  Abstract: A protograph-based low-density parity-check (LDPC) code design technique for bandwidth-efficient coded modulation is presented. The approach jointly optimizes the LDPC code node degrees and the mapping of the coded bits to the bit-interleaved coded modulation (BICM) bit-channels. For BICM with uniform input and for BICM with probabilistic shaping, binary-input symmetric-output surrogate channels are constructed and used for code design. The constructed codes perform as good as multi-edge type codes of Zhang and Kschischang (2013). For 64-ASK with probabilistic shaping, a blocklength 64800 code is constructed that operates within 0.69 dB of 0.5log(1+SNR) at a spectral efficiency of 4.2 bits/channel use and a frame error rate of 1e-3.

Includes members:
  Member "constant composition distribution matching":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "rate constrained shaping codes for structured sources")
  Member "optimized bit mappings for spatially coupled ldpc codes over parallel binary erasure channels":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "optimization of bit mapping and quantized decoding for off the shelf protograph ldpc codes with application to ieee 802 3ca")
  Member "improving soft fec performance for higher order modulations via optimized bit channel mappings":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "optimization of bit mapping and quantized decoding for off the shelf protograph ldpc codes with application to ieee 802 3ca")
  Member "achievable rates for shaped bit metric decoding":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "achievable information rates for probabilistic amplitude shaping a minimum randomness approach via random sign coding arguments")
  Member "probabilistic signal shaping for bit metric decoding":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "achievable information rates for probabilistic amplitude shaping a minimum randomness approach via random sign coding arguments")

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)