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 "channel upgradation for non binary input alphabets and macs"):
  Abstract: Consider a single-user or multiple-access channel with a large output alphabet. A method to approximate the channel by an upgraded version having a smaller output alphabet is presented and analyzed. The original channel is not necessarily symmetric and does not necessarily have a binary input alphabet. Also, the input distribution is not necessarily uniform. The approximation method is instrumental when constructing capacity achieving polar codes for an asymmetric channel with a non-binary input alphabet. Other settings in which the method is instrumental are the wiretap setting as well as the lossy source coding setting.

Includes members:
  Member "construction of polar codes for arbitrary discrete memoryless channels":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "polar codes and their quantum domain counterparts")
  Member "on the construction of polar codes for channels with moderate input alphabet sizes":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "universal polarization for processes with memory")
  Member "how to achieve the capacity of asymmetric channels":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "explicit codes for the wiretap channel a unified design framework")
  Member "upgraded approximation of non binary alphabets for polar code construction":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "construction of polar codes for arbitrary discrete memoryless channels")
  Member "polar codes for the two user multiple access channel":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "polar codes simplicity random codes durability")
  Member "on the construction of polar codes":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "polar codes and their quantum domain counterparts")
  Member "how to construct polar codes":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "polar codes and their quantum domain counterparts")
  Member "achieving the secrecy capacity of wiretap channels using polar codes":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "explicit codes for the wiretap channel a unified design framework")

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)