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: "threshold saturation via spatial coupling why convolutional ldpc ensembles perform so well over the bec"
  Abstract: Convolutional low-density parity-check (LDPC) ensembles, introduced by Felstrom and Zigangirov, have excellent thresholds and these thresholds are rapidly increasing functions of the average degree. Several variations on the basic theme have been proposed to date, all of which share the good performance characteristics of convolutional LDPC ensembles. We describe the fundamental mechanism that explains why “convolutional-like” or “spatially coupled” codes perform so well. In essence, the spatial coupling of individual codes increases the belief-propagation (BP) threshold of the new ensemble to its maximum possible value, namely the maximum a posteriori (MAP) threshold of the underlying ensemble. For this reason, we call this phenomenon “threshold saturation.” This gives an entirely new way of approaching capacity. One significant advantage of this construction is that one can create capacity-approaching ensembles with an error correcting radius that is increasing in the blocklength. Although we prove the “threshold saturation” only for a specific ensemble and for the binary erasure channel (BEC), empirically the phenomenon occurs for a wide class of ensembles and channels. More generally, we conjecture that for a large range of graphical systems a similar saturation of the “dynamical” threshold occurs once individual components are coupled sufficiently strongly. This might give rise to improved algorithms and new techniques for analysis.

Connected through hyperedge HE-1 (induced by source paper "capacity achieving spatially coupled sparse superposition codes with amp decoding"):
  with members:
    - "sparse regression codes"
    - "the error probability of sparse superposition codes with approximate message passing decoding"
    - "spatially coupled sparse regression codes design and state evolution analysis"
    - "finite sample analysis of approximate message passing algorithms"
    - "techniques for improving the finite length performance of sparse superposition codes"
    - "approximate message passing decoder and capacity achieving sparse superposition codes"
    - "capacity achieving sparse superposition codes via approximate message passing decoding"
    - "universal sparse superposition codes with spatial coupling and gamp decoding"

Connected through hyperedge HE-2 (induced by source paper "peeling close to the orientability threshold spatial coupling in hashing based data structures"):
  with members:
    - "dense peelable random uniform hypergraphs"
    - "fast scalable construction of minimal perfect hash functions"
    - "bubing massive crawling for the masses"
    - "the multiple orientability thresholds for random hypergraphs"
    - "on the insertion time of random walk cuckoo hashing"
    - "high speed hashing for integers and strings"
    - "cache oblivious peeling of random hypergraphs"
    - "thresholds of spatially coupled systems via lyapunov s method"

Connected through hyperedge HE-3 (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"
    - "wave like decoding of tail biting spatially coupled ldpc codes through iterative demapping"
    - "finite length analysis of spatially coupled regular ldpc ensembles on burst erasure channels"
    - "efficient multi dimensional mapping using qam constellations for bicm id"

Connected through hyperedge HE-4 (induced by source paper "finite length scaling of spatially coupled ldpc codes under window decoding over the bec"):
  with members:
    - "spatially coupled turbo like codes"
    - "a scaling law to predict the finite length performance of spatially coupled ldpc codes"
    - "spatially coupled sparse codes on graphs theory and practice"
    - "spatially coupled ensembles universally achieve capacity under belief propagation"
    - "lossy source coding via spatially coupled ldgm ensembles"
    - "windowed decoding of protograph based ldpc convolutional codes over erasure channels"
    - "staircase codes fec for 100 gb s otn"
    - "information theoretically optimal compressed sensing via spatial coupling and approximate message passing"

Connected through hyperedge HE-5 (induced by source paper "non uniform windowed decoding for multi dimensional spatially coupled ldpc codes"):
  with members:
    - "minimizing the number of detrimental objects in multi dimensional graph based codes"
    - "finite length analysis of spatially coupled regular ldpc ensembles on burst erasure channels"
    - "new codes on graphs constructed by connecting spatially coupled chains"
    - "spatially coupled ensembles universally achieve capacity under belief propagation"
    - "windowed decoding of protograph based ldpc convolutional codes over erasure channels"
    - "windowed decoding of spatially coupled codes"

Connected through hyperedge HE-6 (induced by source paper "systematic convolutional low density generator matrix code"):
  with members:
    - "systematic block markov superposition transmission of repetition codes"
    - "threshold saturation for spatially coupled ldpc and ldgm codes on bms channels"
    - "block markov superposition transmission construction of big convolutional codes from short codes"
    - "spatially coupled ensembles universally achieve capacity under belief propagation"
    - "threshold saturation on bms channels via spatial coupling"
    - "channel polarization a method for constructing capacity achieving codes for symmetric binary input memoryless channels"

Connected through hyperedge HE-7 (induced by source paper "generalized ldpc codes with convolutional code constraints"):
  with members:
    - "spatially coupled turbo like codes a new trade off between waterfall and error floor"
    - "spatially coupled turbo like codes"
    - "a simple proof of maxwell saturation for coupled scalar recursions"
    - "the generalized area theorem and some of its consequences"

Connected through hyperedge HE-8 (induced by source paper "lattice coding for downlink multiuser transmission"):
  with members:
    - "downlink non orthogonal multiple access without sic for block fading channels an algebraic rotation approach"
    - "joint pilot and payload power control for uplink mimo noma with mrc sic receivers"
    - "short packet downlink transmission with non orthogonal multiple access"
    - "a multi beam noma framework for hybrid mmwave systems"
    - "optimal resource allocation for power efficient mc noma with imperfect channel state information"
    - "improved decoding and error floor analysis of staircase codes"
    - "performance analysis of a hybrid downlink uplink cooperative noma scheme"
    - "on non orthogonal multiple access with finite alphabet inputs in z 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)