Genetic algorithm based resource allocation technique for VLC networks

Title Genetic algorithm based resource allocation technique for VLC networks
Author Demir, Muhammet Selim, Gemici, Ö. F., Uysal, Murat
Publication Date: 2017
Publication Place - IEEE
Subject Visible light communications, Resource allocation, Genetic algorithm, Visible light communications, Resource allocation, Genetic algorithm, DCO-OFDM
Type Document
Language Turkish
Digital Yes
Manuscript No
Library: Özyeğin University
Library Asset ID 978-1-5090-6494-6
Record ID 5086977c-96c8-44a1-8b8a-a6c35d6594b3
Library Location Electrical & Electronics Engineering
Date 2017
Notes Due to copyright restrictions, the access to the full text of this article is only available via subscription.
Sample Text In this study, a genetic algorithm (GA) based resource allocation technique is proposed for visible light communication (VLC) networks. The optical VLC network consists of very small-sized cells in interior spaces where existing lighting infrastructure is used. Effective resource allocation mechanisms are needed in VLC networks to increase system capacity and distribute resources more equitably among users. Therefore, in this study, it is aimed to maximize the total channel capacity by proposing a GA-based resource allocation technique. The proposed resource allocation algorithm gave better results in terms of increasing system capacity compared to Round Robin and Best CQI algorithms., In this paper, we present a genetic algorithm (GA) based resource allocation technique for indoor optical visible light communication (VLC) networks. Optical VLC network using existing lighting infrastructure in an indoor environment is a cellular network with very small size cells. It is necessary to have effective resource allocation mechanisms for VLC networks to maximize system throughput and fairness among users. We propose a GA based resource allocation scheme to improve total system throughput. Our proposed scheme gives better results compared to Round Robin and Best CQI algorithms in terms of system throughput.
DOI 10.1109/SIU.2017.7960526
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Genetic algorithm based resource allocation technique for VLC networks

Author Demir, Muhammet Selim, Gemici, Ö. F., Uysal, Murat
Publication Date 2017
Publication Place - IEEE
Subject Visible light communications, Resource allocation, Genetic algorithm, Visible light communications, Resource allocation, Genetic algorithm, DCO-OFDM
Type Document
Language Turkish
Digital Yes
Manuscript No
Library Özyeğin University
Library Asset ID 978-1-5090-6494-6
Record ID 5086977c-96c8-44a1-8b8a-a6c35d6594b3
Library Location Electrical & Electronics Engineering
Date 2017
Notes Due to copyright restrictions, the access to the full text of this article is only available via subscription.
Sample Text In this study, a genetic algorithm (GA) based resource allocation technique is proposed for visible light communication (VLC) networks. The optical VLC network consists of very small-sized cells in interior spaces where existing lighting infrastructure is used. Effective resource allocation mechanisms are needed in VLC networks to increase system capacity and distribute resources more equitably among users. Therefore, in this study, it is aimed to maximize the total channel capacity by proposing a GA-based resource allocation technique. The proposed resource allocation algorithm gave better results in terms of increasing system capacity compared to Round Robin and Best CQI algorithms., In this paper, we present a genetic algorithm (GA) based resource allocation technique for indoor optical visible light communication (VLC) networks. Optical VLC network using existing lighting infrastructure in an indoor environment is a cellular network with very small size cells. It is necessary to have effective resource allocation mechanisms for VLC networks to maximize system throughput and fairness among users. We propose a GA based resource allocation scheme to improve total system throughput. Our proposed scheme gives better results compared to Round Robin and Best CQI algorithms in terms of system throughput.
DOI 10.1109/SIU.2017.7960526
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