English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Phase modulation is a commonly used modulation mode in digital communication,which usually brings phase sparsity to digital signals. It is naturally toconnect the sparsity with the newly emerged theory of compressed sensing (CS),which enables sub-Nyquist sampling of high-bandwidth to sparse signals. For thepresent, applications of CS theory in communication field mainly focus onspectrum sensing, sparse channel estimation etc. Few of current researches takethe phase sparse character into consideration. In this paper, we establish thenovel model of phase modulation signals based on phase sparsity, and introduceCS theory to the phase domain. According to CS theory, rather than thebandwidth, the sampling rate required here is scaling with the symbol rate,which is usually much lower than the Nyquist rate. In this paper, we provideanalytical support for the model, and simulations verify its validity.

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