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

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dc.citedby3
dc.contributor.authorDoroody C.en_US
dc.contributor.authorTiong S.K.en_US
dc.contributor.authorDarzi S.en_US
dc.contributor.authorid56905467200en_US
dc.contributor.authorid15128307800en_US
dc.contributor.authorid55651612500en_US
dc.date.accessioned2023-05-29T06:00:00Z
dc.date.available2023-05-29T06:00:00Z
dc.date.issued2015
dc.descriptionAntennas; Arts computing; Beamforming; Bioluminescence; Energy efficiency; Fire protection; Image processing; Optimization; Signal interference; Signal to noise ratio; Beamforming technique; Business optimization; Firefly algorithms; Industrial optimization; Linear constrained minimum variances; Linearly constrained minimum variance; Meta heuristic algorithm; Signal to interference plus noise ratio; Iterative methodsen_US
dc.description.abstractThis 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. � 2015 IEEE.en_US
dc.description.natureFinalen_US
dc.identifier.ArtNo7219615
dc.identifier.doi10.1109/I4CT.2015.7219615
dc.identifier.epage445
dc.identifier.scopus2-s2.0-84944411845
dc.identifier.spage441
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84944411845&doi=10.1109%2fI4CT.2015.7219615&partnerID=40&md5=5a1f6164165017286381446ac2586aeb
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/22286
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.sourceScopus
dc.sourcetitleI4CT 2015 - 2015 2nd International Conference on Computer, Communications, and Control Technology, Art Proceeding
dc.titleSINR improvement using Firefly Algorithm (FA) for Linear Constrained Minimum Variance (LCMV) beamforming techniqueen_US
dc.typeConference Paperen_US
dspace.entity.typePublication
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