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: "list decoding for nested lattices and applications to relay channels"
  Abstract: We demonstrate a decoding scheme for nested lattice codes which is able to decode a list of a particular size which contains the transmitted codeword with high probability. This list decoder is analogous to that used in random coding arguments in achievability schemes of relay channels, and allows for the effective combination of information from the relay and source node. Using this list decoding result, we demonstrate 1) that lattice codes may achieve the capacity of the physically degraded AWGN relay channel, 2) an achievable rate region for the two-way relay channel with direct links using lattice codes, and 3) that we may improve the constant gap to capacity for specific cases of the two-way relay channel with direct links.

Connected through hyperedge HE-1 (induced by source paper "multilevel coding schemes for compute and forward with flexible decoding"):
  with members:
    - "an algebraic approach to physical layer network coding"
    - "spatially coupled ensembles universally achieve capacity under belief propagation"
    - "divide and conquer approaching the capacity of the two pair bidirectional gaussian relay network"
    - "wireless network information flow a deterministic approach"
    - "reliable physical layer network coding"
    - "threshold saturation via spatial coupling why convolutional ldpc ensembles perform so well over the bec"
    - "universality for the noisy slepian wolf problem via spatial coupling"
    - "universal codes for the gaussian mac via spatial coupling"

Connected through hyperedge HE-2 (induced by source paper "reliable physical layer network coding"):
  with members:
    - "an algebraic approach to physical layer network coding"
    - "divide and conquer approaching the capacity of the two pair bidirectional gaussian relay network"
    - "wireless network information flow a deterministic approach"
    - "nested lattice codes for gaussian relay networks with interference"
    - "on achieving local view capacity via maximal independent graph scheduling"
    - "the approximate capacity of the many to one and one to many gaussian interference channels"
    - "capacity theorems for the awgn multi way relay channel"
    - "noisy network coding"

Connected through hyperedge HE-3 (induced by source paper "lattice codes for the gaussian relay channel decode and forward and compress and forward"):
  with members:
    - "the approximate sum capacity of the symmetric gaussian k user interference channel"
    - "wireless network information flow a deterministic approach"
    - "reliable physical layer network coding"
    - "nested lattice codes for gaussian relay networks with interference"
    - "computation alignment capacity approximation without noise accumulation"
    - "structured interference mitigation in two hop networks"
    - "a lattice compress and forward scheme"
    - "interference alignment at finite snr for time invariant channels"

Connected through hyperedge HE-4 (induced by source paper "structured interference mitigation in two hop networks"):
  with members:
    - "nested lattice codes for gaussian relay networks with interference"
    - "bounds on the capacity of the relay channel with noncausal state information at source"
    - "capacity of the gaussian two way relay channel to within 1 2 bit"
    - "lattice strategies for the dirty multiple access channel"
    - "compute and forward harnessing interference through structured codes"
    - "joint physical layer coding and network coding for bi directional relaying"
    - "on the role of mmse estimation in approaching the information theoretic limits of linear gaussian channels shannon meets wiener"

Connected through hyperedge HE-5 (induced by source paper "a lattice compress and forward scheme"):
  with members:
    - "nested lattice codes for gaussian relay networks with interference"
    - "noisy network coding"
    - "lecture notes on network information theory"
    - "compute and forward harnessing interference through structured codes"
    - "a layered lattice coding scheme for a class of three user gaussian interference channels"
    - "on the role of mmse estimation in approaching the information theoretic limits of linear gaussian channels shannon meets wiener"

Connected through hyperedge HE-6 (induced by source paper "decode forward and compute forward coding schemes for the two way relay channel"):
  with members:
    - "compute and forward harnessing interference through structured codes"
    - "joint physical layer coding and network coding for bi directional relaying"

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)