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: "design of robust protograph based ldpc codes for rate adaptation via probabilistic shaping"
  Abstract: In this work, the design of robust, protograph-based low-density parity-check (LDPC) codes for rate-adaptive communication via probabilistic shaping is considered. Recently, probabilistic amplitude shaping (PAS) by Bocherer et al. has been introduced for capacity approaching and rate-adaptive communication with a bitwise-demapper and binary decoder. Previous work by the authors considered the optimization of protograph based LDPC codes for PAS and specific spectral efficiencies (SEs) to jointly optimize the LDPC code node degrees and the mapping of the coded bits to the bit-interleaved coded modulation (BICM) bit-channels. We show that these codes tend to perform poor when operated at other rates and propose the design of robust LDPC codes by employing a min-max approach in the search for good protograph ensembles via differential evolution. The considered design uses a single 16 amplitude-shift-keying (ASK) constellation and a robust 13/16 rate LDPC code to operate between 0.7 to 2.7 bits per channel use. For a blocklength of 16224 bits and a target frame error rate of 1e-3 the proposed code operates within 1.32 dB of continuous AWGN capacity for 0.7 to 1.3 bpcu and within 1.05 dB for 1.3 bpcu to 2.7 bpcu.

Connected through hyperedge HE-1 (induced by source paper "comparison of geometric and probabilistic shaping with application to atsc 3 0"):
  with members:
    - "approaching the gaussian channel capacity with apsk constellations"
    - "constant composition distribution matching"
    - "constellation design for transmission over nonlinear satellite channels"
    - "constellation shaping for bit interleaved ldpc coded apsk"
    - "design and analysis of nonbinary ldpc codes for arbitrary discrete memoryless 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)