Apr 13, 2020 · This article considers the problem of two-dimensional (2-D) angle estimation of incoherently distributed (ID) sources in massive MIMO ...

This article shows that the matrix representing the 2-D spatial spectrum of ID sources is of low-rank rather than sparse, and forms a rank minimization ...

Jun 18, 2020 · Low-rank matrix recovery theory was inspired by CS, and therefore has strong parallels with the CS framework [33]. In a sense, the low-rankness ...

Spatial Spectrum Estimation of Incoherently Distributed Sources Based on Low-Rank Matrix Recovery. J. Li, F. Chen, Y. Wang, P. Chargé, F. Ji, and H. Yu.

Bibliographic details on Spatial Spectrum Estimation of Incoherently Distributed Sources Based on Low-Rank Matrix Recovery.

We propose a method to estimate joint angular-frequency distribution for incoherently distributed wideband sources via spatio-temporal sparse sampling and low- ...

We propose a method to localize incoherently distributed near-field sources (IDNF) based on a low-rank matrix recovery method.

This paper considers the problem of twodimensional (2-D) angle estimation of incoherently distributed (ID) sources in massive MIMO systems. We first show that ...

TITLE = {Spatial Spectrum Estimation of Incoherently Distributed Sources Based on Low-rank Matrix Recovery}, AUTHOR = {Li, Jie and Chen, Fangjiong and Wang ...

This article considers the problem of joint angular-frequency distribution (JAFD) estimation for incoherently distributed wideband (IDW) sources.