human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "a comparison of superposition coding schemes"
  Abstract: There are two variants of superposition coding schemes. Cover's original superposition coding scheme has code clouds of identical shape, while Bergmans's superposition coding scheme has code clouds of independently generated shapes. These two schemes yield identical achievable rate regions in several scenarios, such as the capacity region for degraded broadcast channels. This paper shows that under optimal decoding, these two superposition coding schemes can result in different rate regions. In particular, it is shown that for the two-receiver broadcast channel, Cover's scheme achieves a larger rate region than Bergmans's scheme in general.

Connected through hyperedge HE-1 (induced by source paper "sliding window superposition coding two user interference channels"):
  with members:
    - "optimal achievable rates for interference networks with random codes"
    - "polar coding for interference networks"
    - "is non unique decoding necessary"
    - "rate splitting in the presence of multiple receivers"
    - "universal codes for the gaussian mac via spatial coupling"
    - "a new outer bound and the noisy interference sum rate capacity for gaussian interference channels"
    - "to decode the interference or to consider it as noise"

Connected through hyperedge HE-2 (induced by source paper "polar coding strategies for the interference channel with partially joint decoding"):
  with members:
    - "achieving the uniform rate region of general multiple access channels by polar coding"
    - "polar coding for processes with memory"
    - "optimal achievable rates for interference networks with random codes"
    - "polar codes for broadcast channels"
    - "polar coding for the broadcast channel with confidential messages a random binning analogy"
    - "how to achieve the capacity of asymmetric channels"
    - "polar coding for interference networks"
    - "channel upgradation for non binary input alphabets and macs"

Connected through hyperedge HE-3 (induced by source paper "polar codes for broadcast channels"):
  with members:
    - "achieving marton s region for broadcast channels using polar codes"
    - "polar codes for the two user multiple access channel"
    - "evaluation of marton s inner bound for the general broadcast channel"
    - "polar codes for q ary channels q 2 r"
    - "how to construct polar codes"
    - "achieving the secrecy capacity of wiretap channels using polar codes"
    - "multilevel polarization of polar codes over arbitrary discrete memoryless channels"
    - "channel polarization on q ary discrete memoryless channels by arbitrary kernels"

Connected through hyperedge HE-4 (induced by source paper "multicoding schemes for interference channels"):
  with members:
    - "on the capacity of the two user gaussian causal cognitive interference channel"
    - "on the achievable rate regions for state dependent gaussian interference channel"
    - "simultaneous nonunique decoding is rate optimal"
    - "wireless network information flow a deterministic approach"
    - "the state dependent semideterministic broadcast channel"
    - "interference channels with source cooperation"
    - "interference channels with destination cooperation"
    - "interference mitigation through limited transmitter cooperation"

Connected through hyperedge HE-5 (induced by source paper "optimal achievable rates for interference networks with random codes"):
  with members:
    - "wireless network information flow a deterministic approach"
    - "interference decoding for deterministic channels"
    - "to decode the interference or to consider it as noise"

Connected through hyperedge HE-6 (induced by source paper "superposition coding is almost always optimal for the poisson broadcast channel"):
  with members:
    - "on broadcast channels with binary inputs and symmetric outputs"
    - "the poisson channel with side information"
    - "capacity regions of two new classes of 2 receiver broadcast channels"

Connected through hyperedge HE-7 (induced by source paper "achieving marton s region for broadcast channels using polar codes"):
  with members:
    - "achieving the uniform rate region of general multiple access channels by polar coding"
    - "polar codes for broadcast channels"
    - "universal polar codes for more capable and less noisy channels and sources"
    - "polar coding for interference networks"
    - "achieving the uniform rate region of multiple access channels using polar codes"
    - "polar codes for arbitrary dmcs and arbitrary macs"
    - "universal polar codes"
    - "rate dependent analysis of the asymptotic behavior of channel polarization"

Connected through hyperedge HE-8 (induced by source paper "polar coding for interference networks"):
  with members:
    - "universal polar codes"
    - "the compound capacity of polar codes"
    - "polarization for arbitrary discrete memoryless channels"

Question: Please tell me which class the center node 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)