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20102021
most citedSparse Multipath Channel Estimation Using Compressive Sampling Matching Pursuit Algorithm

44 citations · 100 across the 27 of their papers we have counts for

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26 papers · 1 filter

cs.IT2014

Automatic Modulation Recognition of PSK Signals with Sub-Nyquist Sampling Based on High Order Statistics

Zhengli Xing, Jie Zhou, Jiangfeng Ye +4

Sampling rate required in the Nth Power Nonlinear Transformation (NPT) method is typically much greater than Nyquist rate, which causes heavy burden for the Analog to Digital Conve…

cs.IT2014

Automatic Modulation Recognition of PSK Signals Using Nonuniform Compressive Samples Based on High Order Statistics

Zhengli Xing, Jie Zhou, Jiangfeng Ye +3

Phase modulation is a commonly used modulation mode in digital communication, which usually brings phase sparsity to digital signals. It is naturally to connect the sparsity with t…

cs.IT2014

A Novel Compressed Sensing Based Model for Reconstructing Sparse Signals Using Phase Sparse Character

Zhengli Xing, Jie Zhou, Jiangfeng Ye +3

Phase modulation is a commonly used modulation mode in digital communication, which usually brings phase sparsity to digital signals. It is naturally to connect the sparsity with t…

cs.IT2012★ 2 cited

Strongly Convex Programming for Principal Component Pursuit

Qingshan You, Qun Wan, Yipeng Liu

In this paper, we address strongly convex programming for princi- pal component pursuit with reduced linear measurements, which decomposes a superposition of a low-rank matrix and…

cs.IT2012★ 1 cited

A Fast HRRP Synthesis Algorithm with Sensing Dictionary in GTD Model

Rong Fan, Qun Wan, Xiao Zhang +2

To achieve high range resolution profile (HRRP), the geometric theory of diffraction (GTD) parametric model is widely used in stepped-frequency radar system. In the paper, a fast s…

cs.IT2012★ 6 cited

Complex Orthogonal Matching Pursuit and Its Exact Recovery Conditions

Rong Fan, Qun Wan, Yipeng Liu +2

In this paper, we present new results on using orthogonal matching pursuit (OMP), to solve the sparse approximation problem over redundant dictionaries for complex cases (i.e., com…