DOA estimation in MIMO systems with Compressive Sensing for future handsets

Saleh A. Alawsh; Ali H. Muqaibel; Mohammad S. Sharawi

doi:10.1109/AEECT.2015.7360532

DOA estimation in MIMO systems with Compressive Sensing for future handsets

Saleh A. Alawsh
, Ali H. Muqaibel
, Mohammad S. Sharawi

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

4 Scopus citations

Abstract

Future handsets are characterized by their small size which limits the number of antennas and the spacing between them. This paper mainly focuses on Direction-of-Arrival (DOA) estimation in Multiple-Input-Multiple-Output (MIMO) systems based on Compressive Sensing (CS) with practical limitations. The main objective is to strike an optimal balance between complexity and accuracy. A comparison between important DOA estimation algorithms is presented including: Beamforming, Capon, MUSIC, and l1-Singular Value Decomposition (l1-SVD). When considering two antennas with practical antenna spacing limitations, simulation shows that the Root Mean Squared Error (RMSE) of the estimated DOAs is approximately the same for all algorithms in the presence of a single source. The smallest RMSEs are achieved when the spacing between the antennas relative to the wavelength = 1/3. The l1-SVD algorithm is recommended due to the narrow beamwidth and high resolution.

Original language	English
Title of host publication	2015 IEEE Jordan Conference on Applied Electrical Engineering and Computing Technologies, AEECT 2015
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781479974313
DOIs	https://doi.org/10.1109/AEECT.2015.7360532
State	Published - 17 Dec 2015

Publication series

Name	2015 IEEE Jordan Conference on Applied Electrical Engineering and Computing Technologies, AEECT 2015

Bibliographical note

Publisher Copyright:
© 2015 IEEE.

Keywords

Beamforming
Beamwidth
Capone
Compressive Sensing
Direction-of-arrival estimation
MUltiple SIgnal Classification (MUSIC)
Root Mean Sqaured Error (RMSE)
Source Localization

ASJC Scopus subject areas

Electrical and Electronic Engineering
Computer Networks and Communications
Hardware and Architecture
Energy Engineering and Power Technology

Access to Document

10.1109/AEECT.2015.7360532

Cite this

Alawsh, S. A., Muqaibel, A. H., & Sharawi, M. S. (2015). DOA estimation in MIMO systems with Compressive Sensing for future handsets. In 2015 IEEE Jordan Conference on Applied Electrical Engineering and Computing Technologies, AEECT 2015 Article 7360532 (2015 IEEE Jordan Conference on Applied Electrical Engineering and Computing Technologies, AEECT 2015). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/AEECT.2015.7360532

Alawsh, Saleh A. ; Muqaibel, Ali H. ; Sharawi, Mohammad S. / DOA estimation in MIMO systems with Compressive Sensing for future handsets. 2015 IEEE Jordan Conference on Applied Electrical Engineering and Computing Technologies, AEECT 2015. Institute of Electrical and Electronics Engineers Inc., 2015. (2015 IEEE Jordan Conference on Applied Electrical Engineering and Computing Technologies, AEECT 2015).

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title = "DOA estimation in MIMO systems with Compressive Sensing for future handsets",

abstract = "Future handsets are characterized by their small size which limits the number of antennas and the spacing between them. This paper mainly focuses on Direction-of-Arrival (DOA) estimation in Multiple-Input-Multiple-Output (MIMO) systems based on Compressive Sensing (CS) with practical limitations. The main objective is to strike an optimal balance between complexity and accuracy. A comparison between important DOA estimation algorithms is presented including: Beamforming, Capon, MUSIC, and l1-Singular Value Decomposition (l1-SVD). When considering two antennas with practical antenna spacing limitations, simulation shows that the Root Mean Squared Error (RMSE) of the estimated DOAs is approximately the same for all algorithms in the presence of a single source. The smallest RMSEs are achieved when the spacing between the antennas relative to the wavelength = 1/3. The l1-SVD algorithm is recommended due to the narrow beamwidth and high resolution.",

keywords = "Beamforming, Beamwidth, Capone, Compressive Sensing, Direction-of-arrival estimation, MUltiple SIgnal Classification (MUSIC), Root Mean Sqaured Error (RMSE), Source Localization",

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doi = "10.1109/AEECT.2015.7360532",

language = "English",

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Alawsh, SA, Muqaibel, AH & Sharawi, MS 2015, DOA estimation in MIMO systems with Compressive Sensing for future handsets. in 2015 IEEE Jordan Conference on Applied Electrical Engineering and Computing Technologies, AEECT 2015., 7360532, 2015 IEEE Jordan Conference on Applied Electrical Engineering and Computing Technologies, AEECT 2015, Institute of Electrical and Electronics Engineers Inc. https://doi.org/10.1109/AEECT.2015.7360532

DOA estimation in MIMO systems with Compressive Sensing for future handsets. / Alawsh, Saleh A.; Muqaibel, Ali H.; Sharawi, Mohammad S.
2015 IEEE Jordan Conference on Applied Electrical Engineering and Computing Technologies, AEECT 2015. Institute of Electrical and Electronics Engineers Inc., 2015. 7360532 (2015 IEEE Jordan Conference on Applied Electrical Engineering and Computing Technologies, AEECT 2015).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Alawsh, Saleh A.

AU - Muqaibel, Ali H.

AU - Sharawi, Mohammad S.

PY - 2015/12/17

Y1 - 2015/12/17

N2 - Future handsets are characterized by their small size which limits the number of antennas and the spacing between them. This paper mainly focuses on Direction-of-Arrival (DOA) estimation in Multiple-Input-Multiple-Output (MIMO) systems based on Compressive Sensing (CS) with practical limitations. The main objective is to strike an optimal balance between complexity and accuracy. A comparison between important DOA estimation algorithms is presented including: Beamforming, Capon, MUSIC, and l1-Singular Value Decomposition (l1-SVD). When considering two antennas with practical antenna spacing limitations, simulation shows that the Root Mean Squared Error (RMSE) of the estimated DOAs is approximately the same for all algorithms in the presence of a single source. The smallest RMSEs are achieved when the spacing between the antennas relative to the wavelength = 1/3. The l1-SVD algorithm is recommended due to the narrow beamwidth and high resolution.

AB - Future handsets are characterized by their small size which limits the number of antennas and the spacing between them. This paper mainly focuses on Direction-of-Arrival (DOA) estimation in Multiple-Input-Multiple-Output (MIMO) systems based on Compressive Sensing (CS) with practical limitations. The main objective is to strike an optimal balance between complexity and accuracy. A comparison between important DOA estimation algorithms is presented including: Beamforming, Capon, MUSIC, and l1-Singular Value Decomposition (l1-SVD). When considering two antennas with practical antenna spacing limitations, simulation shows that the Root Mean Squared Error (RMSE) of the estimated DOAs is approximately the same for all algorithms in the presence of a single source. The smallest RMSEs are achieved when the spacing between the antennas relative to the wavelength = 1/3. The l1-SVD algorithm is recommended due to the narrow beamwidth and high resolution.

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Alawsh SA, Muqaibel AH, Sharawi MS. DOA estimation in MIMO systems with Compressive Sensing for future handsets. In 2015 IEEE Jordan Conference on Applied Electrical Engineering and Computing Technologies, AEECT 2015. Institute of Electrical and Electronics Engineers Inc. 2015. 7360532. (2015 IEEE Jordan Conference on Applied Electrical Engineering and Computing Technologies, AEECT 2015). doi: 10.1109/AEECT.2015.7360532

DOA estimation in MIMO systems with Compressive Sensing for future handsets

Abstract

Publication series

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

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Cite this