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 "iterative receiver design with off the grid sparse channel estimation"):
  Abstract: In this work we design an iterative receiver that incorporate sparse channel estimation. State-of-the-art sparse channel estimators simplify the estimation problem to be a finite basis selection problem by restricting the multipath delays to a grid. Our main contribution is a receiver that is released from such a restriction; the delays are "off-the-grid", i.e., they are estimated and tracked directly as continuous values. As a result our receiver does not suffer from the leakage effect, which destroys sparsity when the delays are restricted to a grid. We use the unifying framework of combined belief-propagation and mean-field. All parameters in the receiver are inherently estimated. The receiver outperforms iterative receivers embedding state-of-the-art sparse channel estimators in terms of both mean- squared error of the channel estimate and bit error rate. We also demonstrate that our receiver design allows for a significant reduction in the number of pilot signals, without incurring any increase in bit error rate. The receiver also adapts well to situations where the sparse channel assumption is violated; in this case its bit error rate is comparable to that of an iterative receiver that uses minimum mean-squared error channel estimation.

Includes members:
  Member "atomic norm denoising with applications to line spectral estimation":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "convolutional dictionary learning based auto encoders for natural exponential family distributions")
  Member "message passing algorithms for channel estimation and decoding using approximate inference":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "unifying message passing algorithms under the framework of constrained bethe free energy minimization")
  Member "towards a mathematical theory of super resolution":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "approximate support recovery of atomic line spectral estimation a tale of resolution and precision")
  Member "a message passing receiver for bicm ofdm over unknown clustered sparse channels":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "capacity optimality of amp in coded systems")
  Member "merging belief propagation and the mean field approximation a free energy approach":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "dnn aided block sparse bayesian learning for user activity detection and channel estimation in grant free non orthogonal random access")
  Member "compressive estimation of doubly selective channels in multicarrier systems leakage effects and sparsity enhancing processing":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "eliminating impulsive noise in pilot aided ofdm channels via dual of penalized atomic norm")
  Member "a message passing approach for joint channel estimation interference mitigation and decoding":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "coherent detection for short packet physical layer network coding with fsk modulation")
  Member "sufficient conditions for convergence of the sum product algorithm":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "factorized graph representations for semi supervised learning from sparse data")

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)