human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "awgn goodness is enough capacity achieving lattice codes based on dithered probabilistic shaping"):
  Abstract: In this paper we show that any sequence of infinite lattice constellations which is good for the unconstrained Gaussian channel can be shaped into a capacity-achieving sequence of codes for the power-constrained Gaussian channel under lattice decoding and non-uniform signalling. Unlike previous results in the literature, our scheme holds with no extra condition on the lattices (e.g. quantization-goodness or vanishing flatness factor), thus establishing a direct implication between AWGN-goodness, in the sense of Poltyrev, and capacity-achieving codes. Our analysis uses properties of the discrete Gaussian distribution in order to obtain precise bounds on the probability of error and achievable rates. In particular, we obtain a simple characterization of the finite-blocklength behavior of the scheme, showing that it approaches the optimal dispersion coefficient for \textit{high} signal-to-noise ratio. We further show that for \textit{low} signal-to-noise ratio the discrete Gaussian over centered lattice constellations can not achieve capacity, and thus a shift (or "dither") is essentially necessary.

Includes members:
  Member "fundamental limits of communication with low probability of detection":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "keyless covert communication via channel state information")
  Member "covert communication over noisy channels a resolvability perspective":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "keyless covert communication via channel state information")
  Member "on probabilistic shaping of quadrature amplitude modulation for the nonlinear fiber channel":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "analysis and optimization of tail biting spatially coupled protograph ldpc codes for bicm id systems")
  Member "algebraic lattice codes achieve the capacity of the compound block fading channel":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "ring compute and forward over block fading channels")
  Member "lda lattices without dithering achieve capacity on the gaussian channel":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "lattice coding for downlink multiuser transmission")
  Member "almost universal codes for fading wiretap channels":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "well rounded lattices towards optimal coset codes for gaussian and fading wiretap channels")
  Member "construction of capacity achieving lattice codes polar lattices":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "sparse regression codes")
  Member "on the lattice smoothing parameter problem":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "solving the shortest vector problem in 2 n time via discrete gaussian sampling")

Question: Please tell me which class the source paper 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)