SINR improvement using Firefly Algorithm (FA) for Linear Constrained Minimum Variance (LCMV) beamforming technique

Camellia Doroody, Sieh Kiong Tiong, Soodabeh Darzi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

This paper presents the significance of the application of Firefly Algorithm (FA) in the Linearly Constrained Minimum Variance (LCMV) beamforming technique. In this work, in order to obtain the best result, different amounts of parameters such as iteration, null and the boundary have been implemented for more than 30 times. This is done to improve the null steering, signal to interference plus noise ratio (SINR), direction detection and power consumption efficiency. The LCMV beamformer directs the beam radiation through the desired point of user using allocated weight vectors derived from the received signal. However, the weights derived from the received signal by the LCMV method (WLCMV) are not usually focused on the users point accurately. Thus, there will be significant power wastage in other directions rather than the desired users point. Accordingly, here the FA technique is applied into the LCMV beamformer to modify the weights of LCMV. The FA is a metaheuristic algorithm based on the flashing lights of fireflies. It has perfectly solved many problems in almost all engineering fields, such as, image processing, industrial optimization, antenna design and business optimization, etc. The FA method optimizes the light intensity of fireflies by updating the attractiveness and the position of each firefly based on the brightest firefly or the highest light intensity value. Ultimately, all fireflies will gather around the firefly with the highest light intensity value. In this research, results achieved from the optimization of LCMV using FA are simulated in several cases.

Original languageEnglish
Title of host publicationI4CT 2015 - 2015 2nd International Conference on Computer, Communications, and Control Technology, Art Proceeding
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages441-445
Number of pages5
ISBN (Electronic)9781479979523
DOIs
Publication statusPublished - 24 Aug 2015
Event2nd International Conference on Computer, Communications, and Control Technology, I4CT 2015 - Kuching, Sarawak, Malaysia
Duration: 21 Apr 201523 Apr 2015

Publication series

NameI4CT 2015 - 2015 2nd International Conference on Computer, Communications, and Control Technology, Art Proceeding

Other

Other2nd International Conference on Computer, Communications, and Control Technology, I4CT 2015
CountryMalaysia
CityKuching, Sarawak
Period21/04/1523/04/15

Fingerprint

Beamforming
High intensity light
Image processing
Electric power utilization
Antennas
Radiation
Industry

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Computer Networks and Communications
  • Computer Science Applications
  • Software

Cite this

Doroody, C., Tiong, S. K., & Darzi, S. (2015). SINR improvement using Firefly Algorithm (FA) for Linear Constrained Minimum Variance (LCMV) beamforming technique. In I4CT 2015 - 2015 2nd International Conference on Computer, Communications, and Control Technology, Art Proceeding (pp. 441-445). [7219615] (I4CT 2015 - 2015 2nd International Conference on Computer, Communications, and Control Technology, Art Proceeding). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/I4CT.2015.7219615
Doroody, Camellia ; Tiong, Sieh Kiong ; Darzi, Soodabeh. / SINR improvement using Firefly Algorithm (FA) for Linear Constrained Minimum Variance (LCMV) beamforming technique. I4CT 2015 - 2015 2nd International Conference on Computer, Communications, and Control Technology, Art Proceeding. Institute of Electrical and Electronics Engineers Inc., 2015. pp. 441-445 (I4CT 2015 - 2015 2nd International Conference on Computer, Communications, and Control Technology, Art Proceeding).
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abstract = "This paper presents the significance of the application of Firefly Algorithm (FA) in the Linearly Constrained Minimum Variance (LCMV) beamforming technique. In this work, in order to obtain the best result, different amounts of parameters such as iteration, null and the boundary have been implemented for more than 30 times. This is done to improve the null steering, signal to interference plus noise ratio (SINR), direction detection and power consumption efficiency. The LCMV beamformer directs the beam radiation through the desired point of user using allocated weight vectors derived from the received signal. However, the weights derived from the received signal by the LCMV method (WLCMV) are not usually focused on the users point accurately. Thus, there will be significant power wastage in other directions rather than the desired users point. Accordingly, here the FA technique is applied into the LCMV beamformer to modify the weights of LCMV. The FA is a metaheuristic algorithm based on the flashing lights of fireflies. It has perfectly solved many problems in almost all engineering fields, such as, image processing, industrial optimization, antenna design and business optimization, etc. The FA method optimizes the light intensity of fireflies by updating the attractiveness and the position of each firefly based on the brightest firefly or the highest light intensity value. Ultimately, all fireflies will gather around the firefly with the highest light intensity value. In this research, results achieved from the optimization of LCMV using FA are simulated in several cases.",
author = "Camellia Doroody and Tiong, {Sieh Kiong} and Soodabeh Darzi",
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Doroody, C, Tiong, SK & Darzi, S 2015, SINR improvement using Firefly Algorithm (FA) for Linear Constrained Minimum Variance (LCMV) beamforming technique. in I4CT 2015 - 2015 2nd International Conference on Computer, Communications, and Control Technology, Art Proceeding., 7219615, I4CT 2015 - 2015 2nd International Conference on Computer, Communications, and Control Technology, Art Proceeding, Institute of Electrical and Electronics Engineers Inc., pp. 441-445, 2nd International Conference on Computer, Communications, and Control Technology, I4CT 2015, Kuching, Sarawak, Malaysia, 21/04/15. https://doi.org/10.1109/I4CT.2015.7219615

SINR improvement using Firefly Algorithm (FA) for Linear Constrained Minimum Variance (LCMV) beamforming technique. / Doroody, Camellia; Tiong, Sieh Kiong; Darzi, Soodabeh.

I4CT 2015 - 2015 2nd International Conference on Computer, Communications, and Control Technology, Art Proceeding. Institute of Electrical and Electronics Engineers Inc., 2015. p. 441-445 7219615 (I4CT 2015 - 2015 2nd International Conference on Computer, Communications, and Control Technology, Art Proceeding).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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N2 - This paper presents the significance of the application of Firefly Algorithm (FA) in the Linearly Constrained Minimum Variance (LCMV) beamforming technique. In this work, in order to obtain the best result, different amounts of parameters such as iteration, null and the boundary have been implemented for more than 30 times. This is done to improve the null steering, signal to interference plus noise ratio (SINR), direction detection and power consumption efficiency. The LCMV beamformer directs the beam radiation through the desired point of user using allocated weight vectors derived from the received signal. However, the weights derived from the received signal by the LCMV method (WLCMV) are not usually focused on the users point accurately. Thus, there will be significant power wastage in other directions rather than the desired users point. Accordingly, here the FA technique is applied into the LCMV beamformer to modify the weights of LCMV. The FA is a metaheuristic algorithm based on the flashing lights of fireflies. It has perfectly solved many problems in almost all engineering fields, such as, image processing, industrial optimization, antenna design and business optimization, etc. The FA method optimizes the light intensity of fireflies by updating the attractiveness and the position of each firefly based on the brightest firefly or the highest light intensity value. Ultimately, all fireflies will gather around the firefly with the highest light intensity value. In this research, results achieved from the optimization of LCMV using FA are simulated in several cases.

AB - This paper presents the significance of the application of Firefly Algorithm (FA) in the Linearly Constrained Minimum Variance (LCMV) beamforming technique. In this work, in order to obtain the best result, different amounts of parameters such as iteration, null and the boundary have been implemented for more than 30 times. This is done to improve the null steering, signal to interference plus noise ratio (SINR), direction detection and power consumption efficiency. The LCMV beamformer directs the beam radiation through the desired point of user using allocated weight vectors derived from the received signal. However, the weights derived from the received signal by the LCMV method (WLCMV) are not usually focused on the users point accurately. Thus, there will be significant power wastage in other directions rather than the desired users point. Accordingly, here the FA technique is applied into the LCMV beamformer to modify the weights of LCMV. The FA is a metaheuristic algorithm based on the flashing lights of fireflies. It has perfectly solved many problems in almost all engineering fields, such as, image processing, industrial optimization, antenna design and business optimization, etc. The FA method optimizes the light intensity of fireflies by updating the attractiveness and the position of each firefly based on the brightest firefly or the highest light intensity value. Ultimately, all fireflies will gather around the firefly with the highest light intensity value. In this research, results achieved from the optimization of LCMV using FA are simulated in several cases.

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Doroody C, Tiong SK, Darzi S. SINR improvement using Firefly Algorithm (FA) for Linear Constrained Minimum Variance (LCMV) beamforming technique. In I4CT 2015 - 2015 2nd International Conference on Computer, Communications, and Control Technology, Art Proceeding. Institute of Electrical and Electronics Engineers Inc. 2015. p. 441-445. 7219615. (I4CT 2015 - 2015 2nd International Conference on Computer, Communications, and Control Technology, Art Proceeding). https://doi.org/10.1109/I4CT.2015.7219615