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 "on the decoding of polar codes on permuted factor graphs"):
  Abstract: Polar codes are a channel coding scheme for the next generation of wireless communications standard (5G). The belief propagation (BP) decoder allows for parallel decoding of polar codes, making it suitable for high throughput applications. However, the error-correction performance of polar codes under BP decoding is far from the requirements of 5G. It has been shown that the error-correction performance of BP can be improved if the decoding is performed on multiple permuted factor graphs of polar codes. However, a different BP decoding scheduling is required for each factor graph permutation which results in the design of a different decoder for each permutation. Moreover, the selection of the different factor graph permutations is at random, which prevents the decoder to achieve a desirable error-correction performance with a small number of permutations. In this paper, we first show that the permutations on the factor graph can be mapped into suitable permutations on the codeword positions. As a result, we can make use of a single decoder for all the permutations. In addition, we introduce a method to construct a set of predetermined permutations which can provide the correct codeword if the decoding fails on the original permutation. We show that for the 5G polar code of length $1024$, the error-correction performance of the proposed decoder is more than $0.25$ dB better than that of the BP decoder with the same number of random permutations at the frame error rate of $10^{-4}$.

Includes members:
  Member "belief propagation decoding of polar codes on permuted factor graphs":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "polar codes and their quantum domain counterparts")
  Member "partitioned list decoding of polar codes analysis and improvement of finite length performance":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "sublinear latency for simplified successive cancellation decoding of polar codes")
  Member "fast and flexible successive cancellation list decoders for polar codes":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "polar codes and their quantum domain counterparts")
  Member "blind detection with polar codes":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "design and implementation of a polar codes blind detection scheme")
  Member "llr based successive cancellation list decoding of polar codes":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "polar codes and their quantum domain counterparts")
  Member "list decoding of polar codes":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "polar codes and their quantum domain counterparts")
  Member "performance of polar codes for channel and source coding":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "polar codes and their quantum domain counterparts")

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)