Cost-Aware Bandits for Efficient Channel Selection in Hybrid Band Networks
Recently, hybrid band communications have received much attention to fulfil the exponentially growing user demands in next-generation communication networks. Still, determining the best band to communicate over is a challenging issue, especially in the dynamic channel conditions in multi-band wirele...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-06-01
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| Series: | Electronics |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2079-9292/11/11/1782 |
| _version_ | 1797493632526188544 |
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| author | Sherief Hashima Kohei Hatano Mostafa M. Fouda Zubair M. Fadlullah Ehab Mahmoud Mohamed |
| author_facet | Sherief Hashima Kohei Hatano Mostafa M. Fouda Zubair M. Fadlullah Ehab Mahmoud Mohamed |
| author_sort | Sherief Hashima |
| collection | DOAJ |
| description | Recently, hybrid band communications have received much attention to fulfil the exponentially growing user demands in next-generation communication networks. Still, determining the best band to communicate over is a challenging issue, especially in the dynamic channel conditions in multi-band wireless systems. In this paper, we manipulate a practical online-learning-based solution for the best band/channel selection in hybrid radio frequency and visible light communication (RF/VLC) wireless systems. The best band selection difficulty is formulated as a multi-armed bandit (MAB) with cost subsidy, in which the learner (transmitter) endeavors not only to increase his total reward (throughput) but also reduce his cost (energy consumption). Consequently, we propose two hybrid band selection (HBS) algorithms, named cost subsidy upper confidence bound (CSUCB-HBS) and cost subsidy Thompson sampling (CSTS-HBS), to efficiently handle this problem and obtain the best band with high throughput and low energy consumption. Extensive simulations confirm that CSTS-/CSUCB-HBS outperform the naive TS/UCB and heuristic HBS approaches regarding energy consumption, energy efficiency, throughput, and convergence speed. |
| first_indexed | 2024-03-10T01:22:49Z |
| format | Article |
| id | doaj.art-4f543552c7c94f31851cb16f90eefb33 |
| institution | Directory Open Access Journal |
| issn | 2079-9292 |
| language | English |
| last_indexed | 2024-03-10T01:22:49Z |
| publishDate | 2022-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Electronics |
| spelling | doaj.art-4f543552c7c94f31851cb16f90eefb332023-11-23T13:55:48ZengMDPI AGElectronics2079-92922022-06-011111178210.3390/electronics11111782Cost-Aware Bandits for Efficient Channel Selection in Hybrid Band NetworksSherief Hashima0Kohei Hatano1Mostafa M. Fouda2Zubair M. Fadlullah3Ehab Mahmoud Mohamed4Computational Learning Theory Team, RIKEN-Advanced Intelligence Project (AIP), Fukuoka 819-0395, JapanComputational Learning Theory Team, RIKEN-Advanced Intelligence Project (AIP), Fukuoka 819-0395, JapanDepartment of Electrical and Computer Engineering, Idaho State University, Pocatello, ID 83209, USADepartment of Computer Science, Lakehead University, Thunder Bay, ON P7B 5E1, CanadaElectrical Engineering Department, College of Engineering, Prince Sattam Bin Abdulaziz University, Wadi Addwasir 11991, Saudi ArabiaRecently, hybrid band communications have received much attention to fulfil the exponentially growing user demands in next-generation communication networks. Still, determining the best band to communicate over is a challenging issue, especially in the dynamic channel conditions in multi-band wireless systems. In this paper, we manipulate a practical online-learning-based solution for the best band/channel selection in hybrid radio frequency and visible light communication (RF/VLC) wireless systems. The best band selection difficulty is formulated as a multi-armed bandit (MAB) with cost subsidy, in which the learner (transmitter) endeavors not only to increase his total reward (throughput) but also reduce his cost (energy consumption). Consequently, we propose two hybrid band selection (HBS) algorithms, named cost subsidy upper confidence bound (CSUCB-HBS) and cost subsidy Thompson sampling (CSTS-HBS), to efficiently handle this problem and obtain the best band with high throughput and low energy consumption. Extensive simulations confirm that CSTS-/CSUCB-HBS outperform the naive TS/UCB and heuristic HBS approaches regarding energy consumption, energy efficiency, throughput, and convergence speed.https://www.mdpi.com/2079-9292/11/11/1782WiGigMABscost subsidyVLCRF |
| spellingShingle | Sherief Hashima Kohei Hatano Mostafa M. Fouda Zubair M. Fadlullah Ehab Mahmoud Mohamed Cost-Aware Bandits for Efficient Channel Selection in Hybrid Band Networks Electronics WiGig MABs cost subsidy VLC RF |
| title | Cost-Aware Bandits for Efficient Channel Selection in Hybrid Band Networks |
| title_full | Cost-Aware Bandits for Efficient Channel Selection in Hybrid Band Networks |
| title_fullStr | Cost-Aware Bandits for Efficient Channel Selection in Hybrid Band Networks |
| title_full_unstemmed | Cost-Aware Bandits for Efficient Channel Selection in Hybrid Band Networks |
| title_short | Cost-Aware Bandits for Efficient Channel Selection in Hybrid Band Networks |
| title_sort | cost aware bandits for efficient channel selection in hybrid band networks |
| topic | WiGig MABs cost subsidy VLC RF |
| url | https://www.mdpi.com/2079-9292/11/11/1782 |
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