Matching pursuit-based singular vectors estimation for large MIMO beamforming

Author

Mengyao Wang ; Xiantao Cheng ; Xiaodong Zhu

Author_Institution

Nat. Key Lab. of Sci. & Technol. on Commun., Univ. of Electron. Sci. & Technol. of China, Chengdu, China

Volume

51

Issue

1

fYear

2015

fDate

1 8 2015

Firstpage

56

Lastpage

57

Abstract

In multiple-input-multiple-output (MIMO) systems, beamforming can maximise the signal-to-noise ratio by using the principal right and left singular vectors of the channel matrix as transmit and receive beam vectors, respectively. A matching pursuit (MP)-based singular vectors estimation (SVE) scheme is proposed, referred to as MP-SVE, for beamforming transmission and detection in large MIMO systems. By judiciously exploiting the specific properties of large MIMO channel matrix, the proposed MP-SVE is able to determine the optimal beamforming vector pair while circumventing the burdensome channel estimation and singular value decomposition. The simulations verify that with the same training overhead, the proposed MP-SVE remarkably outperforms the state-of-the-art counterparts.

Keywords

MIMO communication; array signal processing; channel estimation; iterative methods; singular value decomposition; MIMO beamforming; MIMO channel matrix; MP-SVE; SNR; SVD; channel estimation; left singular vectors; matching pursuit-based singular vectors estimation; multiple-input-multiple-output systems; optimal beamforming vector pair; right singular vectors; signal-to-noise ratio; singular value decomposition;

fLanguage

English

Journal_Title

Electronics Letters

Publisher

iet

ISSN

0013-5194

Type

jour

DOI

10.1049/el.2014.3197

Filename

7006839