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: "wave like decoding of tail biting spatially coupled ldpc codes through iterative demapping"
  Abstract: For finite coupling lengths, terminated spatially coupled low-density parity-check (SC-LDPC) codes show a non-negligible rate-loss. In this paper, we investigate if this rate loss can be mitigated by tail-biting SC-LDPC codes in conjunction with iterative demapping of higher order modulation formats. Therefore, we examine the BP threshold of different coupled and uncoupled ensembles. A comparison between the decoding thresholds approximated by EXIT charts and the density evolution results of the coupled and uncoupled ensemble is given. We investigate the effect and potential of different labelings for such a set-up using per-bit EXIT curves, and exemplify the method for a 16-QAM system, e.g., using set partitioning labelings. A hybrid mapping is proposed, where different sub-blocks use different labelings in order to further optimize the decoding thresholds of tail-biting codes, while the computational complexity overhead through iterative demapping remains small.

Connected through hyperedge HE-1 (induced by source paper "analysis and optimization of tail biting spatially coupled protograph ldpc codes for bicm id systems"):
  with members:
    - "finite length construction of high performance spatially coupled codes via optimized partitioning and lifting"
    - "efficient search of compact qc ldpc and sc ldpc convolutional codes with large girth"
    - "improving the decoding threshold of tailbiting spatially coupled ldpc codes by energy shaping"
    - "compact qc ldpc block and sc ldpc convolutional codes for low latency communications"
    - "design and analysis of time invariant sc ldpc convolutional codes with small constraint length"
    - "finite length analysis of spatially coupled regular ldpc ensembles on burst erasure channels"
    - "efficient multi dimensional mapping using qam constellations for bicm id"
    - "on probabilistic shaping of quadrature amplitude modulation for the nonlinear fiber channel"

Connected through hyperedge HE-2 (induced by source paper "spatially coupled ldpc codes and the multiple access channel"):
  with members:
    - "avoiding burst like error patterns in windowed decoding of spatially coupled ldpc codes"
    - "near gaussian multiple access channel capacity detection and decoding"
    - "spatially coupled ldpc codes constructed from protographs"
    - "spatially coupled ensembles universally achieve capacity under belief propagation"
    - "windowed decoding of spatially coupled codes"

Connected through hyperedge HE-3 (induced by source paper "near capacity detection and decoding code design for dynamic user loads in gaussian multiple access channels"):
  with members:
    - "spatially coupled ldpc codes and the multiple access channel"
    - "capacity achieving iterative lmmse detection for mimo noma systems"
    - "on the performance of non orthogonal multiple access in 5g systems with randomly deployed users"
    - "channel polarization a method for constructing capacity achieving codes for symmetric binary input memoryless channels"
    - "mutual information and minimum mean square error in gaussian channels"

Connected through hyperedge HE-4 (induced by source paper "near gaussian multiple access channel capacity detection and decoding"):
  with members:
    - "channel polarization a method for constructing capacity achieving codes for symmetric binary input memoryless channels"
    - "mutual information and minimum mean square error in gaussian 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)