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Off-grid Variational Bayesian Inference of Line Spectral Estimation from One-bit Samples.
TLDR
This paper studied from one-bit quantized samples where variational line spectral estimation (VALSE) combined expectation propagation (EP) VALSE-EP method is proposed and can be easily extended to solve the LSE with the multiple measurement vectors (MMVs).Abstract:
In this paper, the line spectral estimation (LSE) problem is studied from one-bit quantized samples where variational line spectral estimation (VALSE) combined expectation propagation (EP) VALSE-EP method is proposed. Since the original measurements are heavily quantized, performing the off-grid frequency estimation is very challenging. Referring to the expectation propagation (EP) principle, this quantized model is decomposed as two modules, one is the componentwise minimum mean square error (MMSE) module, the other is the standard linear model where the variational line spectrum estimation (VALSE) algorithm can be performed. The VALSE-EP algorithm iterates between the two modules in a turbo manner. In addition, this algorithm can be easily extended to solve the LSE with the multiple measurement vectors (MMVs). Finally, numerical results demonstrate the effectiveness of the proposed VALSE-EP method.read more
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Bilinear Adaptive Generalized Vector Approximate Message Passing
Xiangming Meng,Jiang Zhu +1 more
TL;DR: A novel algorithm is proposed called the Bilinear Adaptive Generalized Vector Approximate Message Passing (BAd-GVAMP), which extends the recently proposed Bilinears Adaptive Vector AMP algorithm to incorporate arbitrary distributions on the output transform.
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Multidimensional Variational Line Spectra Estimation
TL;DR: In this paper, a multidimensional variational line spectral estimation (MDVALSE) method is proposed to estimate the model order, noise variance and uncertain degrees of frequency estimates.
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Variational Bayesian Inference of Line Spectral Estimation with Multiple Measurement Vectors.
TL;DR: The proposed prior distribution provides a good interpretation of tradeoff between grid and off-grid based methods and numerical results demonstrate the effectiveness of the VALSE method, compared to the state-of-the-art methods in the MMVs setting.
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Gridless Variational Line Spectral Estimation with Multiple Measurement Vector from Quantized Samples
TL;DR: Multi snapshot VALSE-EP (MVALSE-EP) is developed to deal with the LSE from multisnapshot quantized data, to iteratively approximate the quantized model as a sequence of simple multiple pseudo unquantized models sharing the same frequency profile.
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Joint CFO, Gridless Channel Estimation and Data Detection for Underwater Acoustic OFDM Systems.
TL;DR: In this paper, the authors proposed an iterative receiver based on gridless variational Bayesian line spectra estimation (VALSE) named JCCD-VALSE that jointly estimates the CFO, the \emph{c}hannel with high resolution and carries out decoding.
References
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