most citedCompressive Spectrum Sensing Using Sampling-Controlled Block Orthogonal Matching Pursuit

30 citations · 63 across the 7 of their papers we have counts for

collaborators

7 papers

eess.SP2023

Sparsity-Based Channel Estimation Exploiting Deep Unrolling for Downlink Massive MIMO

An Chen, Wenbo Xu, Liyang Lu +1

Massive multiple-input multiple-output (MIMO) enjoys great advantage in 5G wireless communication systems owing to its spectrum and energy efficiency. However, hundreds of antennas…

eess.SP2023★ 1 cited

Joint Radio Frequency Fingerprints Identification via Multi-antenna Receiver

Xiaofang Chen, Wenbo Xu, Yue Wang

In Internet of Things (IoT), radio frequency fingerprints (RFF) technology has been widely used for passive security authentication to identify the special emitter. However, few wo…

eess.SP2022★ 1 cited

Compressive Spectrum Sensing Using Blind-Block Orthogonal Least Squares

Liyang Lu, Wenbo Xu, Yue Wang +1

Compressive sensing (CS) has recently emerged as an extremely efficient technology of the wideband spectrum sensing. In compressive spectrum sensing (CSS), it is necessary to know…

eess.SP2022★ 30 cited

Compressive Spectrum Sensing Using Sampling-Controlled Block Orthogonal Matching Pursuit

Liyang Lu, Wenbo Xu, Yue Wang +1

This paper proposes two novel schemes of wideband compressive spectrum sensing (CSS) via block orthogonal matching pursuit (BOMP) algorithm, for achieving high sensing accuracy in…

eess.SP2022

Downlink Massive MIMO Channel Estimation via Deep Unrolling : Sparsity Exploitations in Angular Domain

An Chen, Wenbo Xu, Liyang Lu +1

In frequency division duplex (FDD) massive MIMO systems, reliable downlink channel estimation is essential for the subsequent data transmission but is realized at the cost of massi…

eess.SP2022★ 10 cited

Blind Orthogonal Least Squares based Compressive Spectrum Sensing

Liyang Lu, Wenbo Xu, Yue Wang +1

As an enabling technique of cognitive radio (CR), compressive spectrum sensing (CSS) based on compressive sensing (CS) can detect the spectrum opportunities from wide frequency ban…

eess.SP2022★ 21 cited

Recovery Conditions of Sparse Signals Using Orthogonal Least Squares-Type Algorithms

L. Lu, W. Xu, Y. Wang +1

Orthogonal least squares (OLS)-type algorithms are efficient in reconstructing sparse signals, which include the well-known OLS, multiple OLS (MOLS) and block OLS (BOLS). In this p…