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: "constellation shaping for bit interleaved ldpc coded apsk"
  Abstract: An energy-efficient approach is presented for shaping a bit-interleaved low-density parity-check (LDPC) coded amplitude phase-shift keying (APSK) system. A subset of the interleaved bits output by a binary LDPC encoder are passed through a nonlinear shaping encoder whose output is more likely to be a zero than a one. The "shaping" bits are used to select from among a plurality of subconstellations, while the unshaped bits are used to select the symbol within the subconstellation. Because the shaping bits are biased, symbols from lower-energy subconstellations are selected more frequently than those from higher-energy subconstellations. An iterative decoder shares information among the LDPC decoder, APSK demapper, and shaping decoder. Information rates are computed for a discrete set of APSK ring radii and shaping bit probabilities, and the optimal combination of these parameters is identified for the additive white Gaussian noise (AWGN) channel. With the assistance of extrinsic-information transfer (EXIT) charts, the degree distributions of the LDPC code are optimized for use with the shaped APSK constellation. Simulation results show that the combination of shaping, degree-distribution optimization, and iterative decoding can achieve a gain in excess of 1 dB in AWGN at a rate of 3 bits/symbol compared with a system that does not use shaping, uses an unoptimized code from the DVB-S2 standard, and does not iterate between decoder and demodulator.

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"
    - "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-2 (induced by source paper "prefix free code distribution matching for probabilistic constellation shaping"):
  with members:
    - "shell mapping for distribution matching"
    - "divergence optimal fixed to fixed length distribution matching with shell mapping"
    - "divergence scaling of fixed length binary output one to one distribution matching"
    - "fixed to variable length resolution coding for target distributions"
    - "matching dyadic distributions to channels"
    - "prefix codes equiprobable words unequal letter costs"

Connected through hyperedge HE-3 (induced by source paper "noncoherent ldpc coded physical layer network coding using multitone fsk"):
  with members:
    - "ldpc code design for noncoherent physical layer network coding"
    - "mapping and coding design for channel coded physical layer network coding"
    - "an iterative noncoherent relay receiver for the two way relay channel"
    - "channel coding and decoding in a relay system operated with physical layer network coding"
    - "physical layer network coding"

Connected through hyperedge HE-4 (induced by source paper "asymptotic comparison of ml and map detectors for multidimensional constellations"):
  with members:
    - "high snr asymptotics of mutual information for discrete constellations with applications to bicm"
    - "on the exact ber of bit wise demodulators for one dimensional constellations"

Connected through hyperedge HE-5 (induced by source paper "comparison of geometric and probabilistic shaping with application to atsc 3 0"):
  with members:
    - "design of robust protograph based ldpc codes for rate adaptation via probabilistic shaping"
    - "approaching the gaussian channel capacity with apsk constellations"
    - "constant composition distribution matching"
    - "constellation design for transmission over nonlinear satellite channels"
    - "design and analysis of nonbinary ldpc codes for arbitrary discrete memoryless channels"

Connected through hyperedge HE-6 (induced by source paper "bandwidth efficient and rate matched low density parity check coded modulation"):
  with members:
    - "protograph based ldpc code design for bit metric decoding"
    - "arithmetic distribution matching"
    - "how to achieve the capacity of asymmetric channels"
    - "achieving awgn channel capacity with lattice gaussian coding"
    - "optimal non uniform mapping for probabilistic shaping"
    - "operating ldpc codes with zero shaping gap"
    - "matching dyadic distributions to channels"

Connected through hyperedge HE-7 (induced by source paper "probabilistic signal shaping for bit metric decoding"):
  with members:
    - "arithmetic distribution matching"
    - "an efficient algorithm to calculate bicm capacity"
    - "operating ldpc codes with zero shaping gap"
    - "optimal alphabets and binary labelings for bicm at low snr"

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)