Widely linear LQCMV beamformer and augmented dual-domain adaptive algorithm

Masahiro Yukawa; Yuki Saito

doi:10.1109/ICICS.2013.6782920

Widely linear LQCMV beamformer and augmented dual-domain adaptive algorithm

Masahiro Yukawa
, Yuki Saito

電気情報工学科

研究成果: Paper › 査読

1 被引用数 (Scopus)

抄録

A widely linear extension of the linearly and quadratically constrained minimum variance (LQCMV) beamformer is presented. By exploiting the pseudocovariance matrix which is complementary second order statistics for the ordinary covariance matrix, the widely linear LQCMV (WL-LQCMV) beamformer attains better performance when the received data is noncircular. Adaptive implementation of WL-LQCMV by the dual-domain adaptive algorithm (DDAA) brings a remarkable advantage of fast convergence. The key points of the convergence analysis of DDAA are elaborated. The simulation results are presented to show the efficacy of our approach.

本文言語	English
DOI	https://doi.org/10.1109/ICICS.2013.6782920
出版ステータス	Published - 2013
イベント	9th International Conference on Information, Communications and Signal Processing, ICICS 2013 - Tainan, Taiwan, Province of China 継続期間: 2013 12月 10 → 2013 12月 13

Other

Other	9th International Conference on Information, Communications and Signal Processing, ICICS 2013
国/地域	Taiwan, Province of China
City	Tainan
Period	13/12/10 → 13/12/13

ASJC Scopus subject areas

コンピュータネットワークおよび通信
情報システム
信号処理

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10.1109/ICICS.2013.6782920

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引用スタイル

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abstract = "A widely linear extension of the linearly and quadratically constrained minimum variance (LQCMV) beamformer is presented. By exploiting the pseudocovariance matrix which is complementary second order statistics for the ordinary covariance matrix, the widely linear LQCMV (WL-LQCMV) beamformer attains better performance when the received data is noncircular. Adaptive implementation of WL-LQCMV by the dual-domain adaptive algorithm (DDAA) brings a remarkable advantage of fast convergence. The key points of the convergence analysis of DDAA are elaborated. The simulation results are presented to show the efficacy of our approach.",

author = "Masahiro Yukawa and Yuki Saito",

year = "2013",

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language = "English",

note = "9th International Conference on Information, Communications and Signal Processing, ICICS 2013 ; Conference date: 10-12-2013 Through 13-12-2013",

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AU - Yukawa, Masahiro

AU - Saito, Yuki

PY - 2013

Y1 - 2013

N2 - A widely linear extension of the linearly and quadratically constrained minimum variance (LQCMV) beamformer is presented. By exploiting the pseudocovariance matrix which is complementary second order statistics for the ordinary covariance matrix, the widely linear LQCMV (WL-LQCMV) beamformer attains better performance when the received data is noncircular. Adaptive implementation of WL-LQCMV by the dual-domain adaptive algorithm (DDAA) brings a remarkable advantage of fast convergence. The key points of the convergence analysis of DDAA are elaborated. The simulation results are presented to show the efficacy of our approach.

AB - A widely linear extension of the linearly and quadratically constrained minimum variance (LQCMV) beamformer is presented. By exploiting the pseudocovariance matrix which is complementary second order statistics for the ordinary covariance matrix, the widely linear LQCMV (WL-LQCMV) beamformer attains better performance when the received data is noncircular. Adaptive implementation of WL-LQCMV by the dual-domain adaptive algorithm (DDAA) brings a remarkable advantage of fast convergence. The key points of the convergence analysis of DDAA are elaborated. The simulation results are presented to show the efficacy of our approach.

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UR - https://www.scopus.com/pages/publications/84899091068#tab=citedBy

U2 - 10.1109/ICICS.2013.6782920

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T2 - 9th International Conference on Information, Communications and Signal Processing, ICICS 2013

Y2 - 10 December 2013 through 13 December 2013

ER -

Widely linear LQCMV beamformer and augmented dual-domain adaptive algorithm

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