Suitable is the best: Least absolute deviation algorithm under high-mobility non-Gaussian noise environments

Guan Gui, Li Xu, Fumiyuki Adachi

研究成果: Conference contribution

抄録

Underdetermined inverse sparse signal reconstruction problems in the presence of non-Gaussian noise interference are often encountered in high-mobility wireless communications and signal processing. These problems can be solved by finding the minimizer of a suitable objective function which consists of a data-fitting term and a regularization term with different mixed-norms. Based on the Gaussian-noise assumption, two mixed norms (i.e. ℓ2/ℓ1 and ℓ/ℓ1) were confirmed as effective as well as stable algorithms for reconstructing sparse signals. However, the two algorithms are unable to reconstruct signal stable under non-Gaussian noise environments. In this paper, we propose a stable least absolute deviation (LAD) algorithm (i.e., ℓ1/ℓ1) for achieving two aspects: exploiting signal sparse structure information as well as mitigating the non-Gaussian noise interference. First of all, regularization parameter of the proposed algorithm is selected via Monte Carlo simulations. Then, experimental results in different non-Gaussian environments are used to demonstrate the effectiveness of the proposed algorithm.

本文言語English
ホスト出版物のタイトル2014 International Workshop on High Mobility Wireless Communications, HMWC 2014
出版社Institute of Electrical and Electronics Engineers Inc.
ページ27-32
ページ数6
ISBN(電子版)9781479956463
DOI
出版ステータスPublished - 2014 12 30
イベント2014 International Workshop on High Mobility Wireless Communications, HMWC 2014 - Beijing, China
継続期間: 2014 11 12014 11 3

出版物シリーズ

名前2014 International Workshop on High Mobility Wireless Communications, HMWC 2014

Other

Other2014 International Workshop on High Mobility Wireless Communications, HMWC 2014
CountryChina
CityBeijing
Period14/11/114/11/3

ASJC Scopus subject areas

  • Computer Networks and Communications

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