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 "how to achieve the capacity of asymmetric channels"):
  Abstract: We survey coding techniques that enable reliable transmission at rates that approach the capacity of an arbitrary discrete memoryless channel. In particular, we take the point of view of modern coding theory and discuss how recent advances in coding for symmetric channels help provide more efficient solutions for the asymmetric case. We consider, in more detail, three basic coding paradigms. #R##N#The first one is Gallager's scheme that consists of concatenating a linear code with a non-linear mapping so that the input distribution can be appropriately shaped. We explicitly show that both polar codes and spatially coupled codes can be employed in this scenario. Furthermore, we derive a scaling law between the gap to capacity, the cardinality of the input and output alphabets, and the required size of the mapper. #R##N#The second one is an integrated scheme in which the code is used both for source coding, in order to create codewords distributed according to the capacity-achieving input distribution, and for channel coding, in order to provide error protection. Such a technique has been recently introduced by Honda and Yamamoto in the context of polar codes, and we show how to apply it also to the design of sparse graph codes. #R##N#The third paradigm is based on an idea of B\"ocherer and Mathar, and separates the two tasks of source coding and channel coding by a chaining construction that binds together several codewords. We present conditions for the source code and the channel code, and we describe how to combine any source code with any channel code that fulfill those conditions, in order to provide capacity-achieving schemes for asymmetric channels. In particular, we show that polar codes, spatially coupled codes, and homophonic codes are suitable as basic building blocks of the proposed coding strategy.

Includes members:
  Member "on the scaling exponent of polar codes for binary input energy harvesting channels":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "polar codes simplicity random codes durability")
  Member "threshold saturation for nonbinary sc ldpc codes on the binary erasure channel":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "a combinatorial methodology for optimizing non binary graph based codes theoretical analysis and applications in data storage")
  Member "construction of polar codes with sublinear complexity":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "decoder tailored polar code design using the genetic algorithm")
  Member "polar codes for broadcast channels":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "polar codes simplicity random codes durability")
  Member "a scaling law to predict the finite length performance of spatially coupled ldpc codes":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "finite length scaling of spatially coupled ldpc codes under window decoding over the bec")
  Member "unified scaling of polar codes error exponent scaling exponent moderate deviations and error floors":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "on the polarizing behavior and scaling exponent of polar codes with product kernels")
  Member "finite length scaling for polar codes":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "reed muller codes theory and algorithms")
  Member "achieving marton s region for broadcast channels using polar codes":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "achieving the uniform rate region of general multiple access channels by polar coding")

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)