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 "binary message passing decoding of product like codes"):
  Abstract: We propose a novel binary message passing decoding algorithm for product-like codes based on bounded distance decoding (BDD) of the component codes. The algorithm, dubbed iterative BDD with scaled reliability (iBDD-SR), exploits the channel reliabilities and is therefore soft in nature. However, the messages exchanged by the component decoders are binary (hard) messages, which significantly reduces the decoder data flow. The exchanged binary messages are obtained by combining the channel reliability with the BDD decoder output reliabilities, properly conveyed by a scaling factor applied to the BDD decisions. We perform a density evolution analysis for generalized low-density parity-check (GLDPC) code ensembles and spatially coupled GLDPC code ensembles, from which the scaling factors of the iBDD-SR for product and staircase codes, respectively, can be obtained. For the white additive Gaussian noise channel, we show performance gains up to $0.29$ dB and $0.31$ dB for product and staircase codes compared to conventional iterative BDD (iBDD) with the same decoder data flow. Furthermore, we show that iBDD-SR approaches the performance of ideal iBDD that prevents miscorrections.

Includes members:
  Member "binary message passing decoding of product codes based on generalized minimum distance decoding":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "on product codes with probabilistic amplitude shaping for high throughput fiber optic systems")
  Member "low complexity concatenated ldpc staircase codes":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "coding for optical communications can we approach the shannon limit with low complexity")
  Member "iterative bounded distance decoding of product codes with scaled reliability":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "on product codes with probabilistic amplitude shaping for high throughput fiber optic systems")
  Member "on low complexity decoding of product codes for high throughput fiber optic systems":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "on product codes with probabilistic amplitude shaping for high throughput fiber optic systems")
  Member "energy efficient soft assisted product decoders":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "on product codes with probabilistic amplitude shaping for high throughput fiber optic systems")
  Member "probabilistic amplitude shaping with hard decision decoding and staircase codes":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "on product codes with probabilistic amplitude shaping for high throughput fiber optic systems")
  Member "achievable information rates for coded modulation with hard decision decoding for coherent fiber optic systems":
    also connected through other hyperedges:
      (none)
  Member "density evolution for deterministic generalized product codes on the binary erasure channel at high rates":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "binary message passing decoding of product codes based on generalized minimum distance decoding")

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)