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 "finite dimensional infinite constellations"):
  Abstract: In the setting of a Gaussian channel without power constraints, proposed by Poltyrev in 1994, the codewords are points in an n-dimensional Euclidean space (an infinite constellation) and the tradeoff between their density and the error probability is considered. The normalized log density (NLD) plays the role of the communication rate, and capacity as well as error exponent bounds for this setting are known. This paper considers the infinite constellation setting in the finite block-length (dimension) regime. A simplified expression for Poltyrev's achievability bound is found and it is shown to be closely related to the sphere converse bound and to a recently proposed achievability bound based on point processes. The bounds are then analyzed asymptotically for growing n: for fixed NLD, the bounds turn out to be extremely tight compared to previous error exponent analysis. For fixed error probability e, it is shown that the gap of the highest achievable NLD to the optimal NLD (Poltyrev's capacity) is approximately √{[1/(2n)]}Q-1(e) , where Q is the standard complementary Gaussian cumulative distribution function, thus extending the channel dispersion analysis to infinite constellations. Connections to the error exponent of the power-constrained Gaussian channel and to the volume-to-noise ratio as a figure of merit are discussed. Finally, the new tight bounds are compared to state-of-the-art coding schemes.

Includes members:
  Member "information theoretic capacity and error exponents of stationary point processes under random additive displacements":
    also connected through other hyperedges:
      (none)
  Member "parallel bit interleaved coded modulation":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "coding and system design for quantize map and forward relaying")
  Member "low density lattice codes":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "neural fuzzy extractors a secure way to use artificial neural networks for biometric user authentication")

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)