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: "signal shaping for bicm at low snr"
  Abstract: The generalized mutual information (GMI) of bit-interleaved coded modulation (BICM) systems, sometimes called the BICM capacity, is investigated at low signal-to-noise ratio (SNR). The combinations of input alphabet, input distribution, and binary labeling that achieve the Shannon limit - 1.59 dB are completely characterized. The main conclusion is that a BICM system with probabilistic shaping achieves the Shannon limit at low SNR if and only if it can be represented as a zero-mean linear projection of a hypercube. Hence, probabilistic shaping offers no extra degrees of freedom to optimize the low-SNR BICM-GMI, in addition to what is provided by geometrical shaping. The analytical conclusions are confirmed by numerical results, which also show that for a fixed input alphabet, probabilistic shaping can improve the BICM-GMI in the low and medium SNR range.

Connected through hyperedge HE-1 (induced by source paper "broadcast coded modulation multilevel and bit interleaved construction"):
  with members:
    - "symmetrical multilevel diversity coding and subset entropy inequalities"
    - "multilevel coding schemes for compute and forward with flexible decoding"
    - "asymmetric multilevel diversity coding and asymmetric gaussian multiple descriptions"

Connected through hyperedge HE-2 (induced by source paper "four dimensional coded modulation with bit wise decoders for future optical communications"):
  with members:
    - "high snr asymptotics of mutual information for discrete constellations with applications to bicm"
    - "improving soft fec performance for higher order modulations via optimized bit channel mappings"
    - "probabilistic signal shaping for bit metric decoding"
    - "design of apsk constellations for coherent optical channels with nonlinear phase noise"
    - "general ber expression for one dimensional constellations"
    - "a pragmatic coded modulation scheme for high spectral efficiency fiber optic communications"
    - "calculation of mutual information for partially coherent gaussian channels with applications to fiber optics"
    - "optimal alphabets and binary labelings for bicm at low snr"

Connected through hyperedge HE-3 (induced by source paper "high snr asymptotics of mutual information for discrete constellations with applications to bicm"):
  with members:
    - "on the exact ber of bit wise demodulators for one dimensional constellations"
    - "general ber expression for one dimensional constellations"
    - "multiple antenna fading coherent channels with arbitrary inputs characterization and optimization of the reliable information transmission rate"
    - "precoding for outage probability minimization on block fading channels"
    - "optimal alphabets and binary labelings for bicm at low snr"
    - "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)