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Variable Dimension Measurement Matrix Construction for Compressive Sampling via m Sequence | Springer Nature Link
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AbstractSignal acquisition in ultra-high frequency is a challenging problem due to high cost of analog-digital converter. While compressed sensing (CS) provides an alternative way to sample signal with low sampling rate, the construction of measurement matrix is still challenging due to hardware complexity and random generation. To address this challenge, a variable dimension deterministic measurement matrix construction method is proposed in this paper based on cross-correlation characteristics of m sequences. Specifically, a lower bound of the spark of measurement matrix is derived theoretically. The proposed measurement matrix construction method is applicable to compressive sampling system to improve the quality of signal reconstruction, especially for modulated wideband converter (MWC) architecture. Simulation results demonstrate that the proposed measurement matrix is superior to random Gauss matrix and random Bernoulli matrix.
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AcknowledgmentsThis work was supported by the Fundamental Research Funds for the Center Universities (Grant No. HIT.MKSTISP.2016 13).
Author informationAuthors and Affiliations Communication Research Center, Harbin Institute of Technology, Harbin, 150001, China
Jingting Xiao, Ruoyu Zhang & Honglin Zhao
Authors Jingting Xiao Ruoyu Zhang Honglin Zhao Corresponding author Correspondence to
Jingting Xiao .
Editor informationEditors and Affiliations Harbin Institute of Technology, Harbin, Heilongjiang, China
Xuemai Gu
Harbin Institute of Technology, Weihai, Heilongjiang, China
Gongliang Liu
Shandong University, Weihai, Heilongjiang, China
Bo Li
Copyright information© 2018 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
