Widely linear LQCMV beamformer and augmented dual-domain adaptive algorithm

Masahiro Yukawa, Yuki Saito

    Research output: Contribution to conferencePaper

    1 Citation (Scopus)

    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.

    Original languageEnglish
    DOIs
    Publication statusPublished - 2013 Jan 1
    Event9th International Conference on Information, Communications and Signal Processing, ICICS 2013 - Tainan, Taiwan, Province of China
    Duration: 2013 Dec 102013 Dec 13

    Other

    Other9th International Conference on Information, Communications and Signal Processing, ICICS 2013
    CountryTaiwan, Province of China
    CityTainan
    Period13/12/1013/12/13

    ASJC Scopus subject areas

    • Computer Networks and Communications
    • Information Systems
    • Signal Processing

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  • Cite this

    Yukawa, M., & Saito, Y. (2013). Widely linear LQCMV beamformer and augmented dual-domain adaptive algorithm. Paper presented at 9th International Conference on Information, Communications and Signal Processing, ICICS 2013, Tainan, Taiwan, Province of China. https://doi.org/10.1109/ICICS.2013.6782920