Controllable Sparse Antenna Array for Adaptive Beamforming
We propose an <inline-formula> <tex-math notation="LaTeX">$l_{0}$ </tex-math></inline-formula>-norm constrained normalized least-mean-square (CNLMS) adaptive beamforming algorithm for controllable sparse antenna arrays. To control the sparsity of the antenna array,...
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IEEE
2019-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/8598876/ |
| _version_ | 1818427938228404224 |
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| author | Wanlu Shi Yingsong Li Luyu Zhao Xiaoguang Liu |
| author_facet | Wanlu Shi Yingsong Li Luyu Zhao Xiaoguang Liu |
| author_sort | Wanlu Shi |
| collection | DOAJ |
| description | We propose an <inline-formula> <tex-math notation="LaTeX">$l_{0}$ </tex-math></inline-formula>-norm constrained normalized least-mean-square (CNLMS) adaptive beamforming algorithm for controllable sparse antenna arrays. To control the sparsity of the antenna array, an <inline-formula> <tex-math notation="LaTeX">$l_{0}$ </tex-math></inline-formula>-norm penalty is used as a constraint in the CNLMS algorithm. The proposed algorithm inherits the advantages of the CNLMS algorithm in beamforming. The <inline-formula> <tex-math notation="LaTeX">$l_{0}$ </tex-math></inline-formula>-norm constraint can force the quantities of antennas to a certain number to control the sparsity by selecting a suitable parameter. In addition, the proposed algorithm accelerates the convergence process compared with the existing algorithms in sparse array beamforming, and its convergence is presented in this paper. To reduce the computation burden, an approximating <inline-formula> <tex-math notation="LaTeX">$l_{0}$ </tex-math></inline-formula>-norm method is employed. The performance of the proposed algorithm is analyzed through simulations for various array configurations. |
| first_indexed | 2024-12-14T14:53:40Z |
| format | Article |
| id | doaj.art-e5cece65c9a34672af6cb8d8c1acee89 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-14T14:53:40Z |
| publishDate | 2019-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-e5cece65c9a34672af6cb8d8c1acee892022-12-21T22:57:04ZengIEEEIEEE Access2169-35362019-01-0176412642310.1109/ACCESS.2018.28898778598876Controllable Sparse Antenna Array for Adaptive BeamformingWanlu Shi0Yingsong Li1https://orcid.org/0000-0003-4175-8945Luyu Zhao2https://orcid.org/0000-0001-8981-9829Xiaoguang Liu3College of Information and Communication Engineering, Harbin Engineering University, Harbin, ChinaCollege of Information and Communication Engineering, Harbin Engineering University, Harbin, ChinaKey Laboratory of Antennas and Microwave Technologies, Xidian University, Xi’an, ChinaElectrical and Computer Engineering, University of California at Davis, Davis, CA, USAWe propose an <inline-formula> <tex-math notation="LaTeX">$l_{0}$ </tex-math></inline-formula>-norm constrained normalized least-mean-square (CNLMS) adaptive beamforming algorithm for controllable sparse antenna arrays. To control the sparsity of the antenna array, an <inline-formula> <tex-math notation="LaTeX">$l_{0}$ </tex-math></inline-formula>-norm penalty is used as a constraint in the CNLMS algorithm. The proposed algorithm inherits the advantages of the CNLMS algorithm in beamforming. The <inline-formula> <tex-math notation="LaTeX">$l_{0}$ </tex-math></inline-formula>-norm constraint can force the quantities of antennas to a certain number to control the sparsity by selecting a suitable parameter. In addition, the proposed algorithm accelerates the convergence process compared with the existing algorithms in sparse array beamforming, and its convergence is presented in this paper. To reduce the computation burden, an approximating <inline-formula> <tex-math notation="LaTeX">$l_{0}$ </tex-math></inline-formula>-norm method is employed. The performance of the proposed algorithm is analyzed through simulations for various array configurations.https://ieeexplore.ieee.org/document/8598876/<italic xmlns:ali="http://www.niso.org/schemas/ali/1.0/" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">l</italic>₀-normsparse controllable arrayNLMS algorithmconstrained adaptive beamforming |
| spellingShingle | Wanlu Shi Yingsong Li Luyu Zhao Xiaoguang Liu Controllable Sparse Antenna Array for Adaptive Beamforming IEEE Access <italic xmlns:ali="http://www.niso.org/schemas/ali/1.0/" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">l</italic>₀-norm sparse controllable array NLMS algorithm constrained adaptive beamforming |
| title | Controllable Sparse Antenna Array for Adaptive Beamforming |
| title_full | Controllable Sparse Antenna Array for Adaptive Beamforming |
| title_fullStr | Controllable Sparse Antenna Array for Adaptive Beamforming |
| title_full_unstemmed | Controllable Sparse Antenna Array for Adaptive Beamforming |
| title_short | Controllable Sparse Antenna Array for Adaptive Beamforming |
| title_sort | controllable sparse antenna array for adaptive beamforming |
| topic | <italic xmlns:ali="http://www.niso.org/schemas/ali/1.0/" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">l</italic>₀-norm sparse controllable array NLMS algorithm constrained adaptive beamforming |
| url | https://ieeexplore.ieee.org/document/8598876/ |
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