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: "ldpc lattice codes for full duplex relay channels"
  Abstract: Low density parity check (LDPC) lattices are obtained from Construction D' and a family of nested binary LDPC codes. We consider an special case of these lattices with one binary LDPC code as underlying code. This special case of LDPC lattices can be obtained by lifting binary LDPC codes using Construction A lattices. The LDPC lattices were the first family of lattices which have efficient decoding in high dimensions. We employ the encoding and decoding of the LDPC lattices in a cooperative transmission framework. We establish two efficient shaping methods based on hypercube shaping and Voronoi shaping, to obtain LDPC lattice codes. Then, we propose the implementation of block Markov encoding for one-way and two-way relay networks using LDPC lattice codes. This entails owning an efficient method for decomposing full-rate codebook into lower rate codebooks. We apply different decomposition schemes for one-way and two-way relay channels which are the altered versions of the decomposition methods of low density lattice codes (LDLCs). Due to the lower complexity of the decoding for LDPC lattices comparing to LDLCs, the complexity of our schemes are significantly lower than the ones proposed for LDLCs. The efficiency of the proposed schemes are presented using simulation results.

Connected through hyperedge HE-1 (induced by source paper "a lattice based joint encryption encoding and modulation scheme"):
  with members:
    - "on the performance of 1 level ldpc lattices"
    - "low density lattice codes"

Connected through hyperedge HE-2 (induced by source paper "fast decoding of low density lattice codes"):
  with members:
    - "message passing decoding of lattices using gaussian mixtures"
    - "low density lattice codes"

Connected through hyperedge HE-3 (induced by source paper "multilevel ldpc lattices with efficient encoding and decoding and a generalization of construction d"):
  with members:
    - "lda lattices without dithering achieve capacity on the gaussian channel"
    - "construction of capacity achieving lattice codes polar lattices"
    - "semantically secure lattice codes for the gaussian wiretap channel"
    - "achieving awgn channel capacity with lattice gaussian coding"
    - "connections between construction d and related constructions of lattices"
    - "on the performance of 1 level ldpc lattices"
    - "strong secrecy on the binary erasure wiretap channel using large girth ldpc codes"
    - "integer forcing linear receivers"

Connected through hyperedge HE-4 (induced by source paper "construction and encoding of qc ldpc codes using group rings"):
  with members:
    - "codes from zero divisors and units in group rings"
    - "channel coding the road to channel capacity"

Connected through hyperedge HE-5 (induced by source paper "lda lattices without dithering achieve capacity on the gaussian channel"):
  with members:
    - "some goodness properties of lda lattices"
    - "construction of capacity achieving lattice codes polar lattices"
    - "lattices over eisenstein integers for compute and forward"
    - "achieving awgn channel capacity with lattice gaussian coding"
    - "on the performance of 1 level ldpc lattices"
    - "spatially coupled ensembles universally achieve capacity under belief propagation"
    - "turbo lattices construction and error decoding performance"
    - "a simple proof for the existence of good pairs of nested lattices"

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)