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 "block markov superposition transmission construction of big convolutional codes from short codes"):
  Abstract: A construction of big convolutional codes from short codes called block Markov superposition transmission (BMST) is proposed. The BMST is very similar to superposition blockMarkov encoding (SBME), which has been widely used to prove multiuser coding theorems. The encoding process of BMST can be as fast as that of the involved short code, while the decoding process can be implemented as an iterative sliding-window decoding algorithm with a tunable delay. More importantly, the performance of BMST can be simply lower-bounded in terms of the transmission memory given that the performance of the short code is available. Numerical results show that, 1) the lower bounds can be matched with a moderate decoding delay in the low bit-error-rate (BER) region, implying that the iterative slidingwindow decoding algorithm is near optimal; 2) BMST with repetition codes and single parity-check codes can approach the Shannon limit within 0.5 dB at BER of 10^{-5} for a wide range of code rates; and 3) BMST can also be applied to nonlinear codes.

Includes members:
  Member "on the minimum distance of generalized spatially coupled ldpc codes":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "spatially coupled generalized ldpc codes asymptotic analysis and finite length scaling")
  Member "spatially coupled ensembles universally achieve capacity under belief propagation":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "capacity achieving spatially coupled sparse superposition codes with amp decoding")
  Member "windowed decoding of protograph based ldpc convolutional codes over erasure channels":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "finite length scaling of spatially coupled ldpc codes under window decoding over the bec")
  Member "threshold saturation via spatial coupling why convolutional ldpc ensembles perform so well over the bec":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "capacity achieving spatially coupled sparse superposition codes with amp decoding")
  Member "new techniques for upper bounding the ml decoding performance of binary linear codes":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "enumeration of minimum hamming weight polar codewords with sublinear complexity")
  Member "serial concatenation of rs codes with kite codes performance analysis iterative decoding and design":
    also connected through other hyperedges:
      (none)
  Member "scaling behavior of convolutional ldpc ensembles over the bec":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "covariance evolution for spatially mt fuji coupled ldpc codes")
  Member "windowed decoding of spatially coupled codes":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "non uniform windowed decoding for multi dimensional spatially coupled ldpc codes")

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)