An Artificial Neural Network-Based Handover Scheme for Hybrid LiFi Networks Article Swipe
YOU?
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· 2022
· Open Access
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· DOI: https://doi.org/10.1109/access.2022.3228570
Combining the ultra-high user throughput of the light fidelity (LiFi) and the ubiquitous coverage of wireless fidelity (WiFi), the hybrid LiFi and WiFi network (HLWNet) demonstrates unparalleled advantages in indoor wireless data transmission. Due to the line-of-sight propagation nature of the optical signal, the handover decision-making problem in HLWNets, however, becomes more critical and challenging than that in previous heterogeneous networks. In this paper, the handover decision-making problem in the HLWNet is regarded as a binary classification problem, and an artificial neural network (ANN)-based handover scheme is proposed. The complete handover scheme consists of two sets of ANNs that use the information about channel quality, user movement, and device orientation as input features to make handover decisions. After being trained with the labeled datasets that are generated with a novel approach, the ANN-based handover scheme is able to achieve over 95% handover accuracy. The proposed scheme is then compared with benchmarks under an indoor simulation scenario. The simulation results show that the proposed approach can significantly increase user throughput by 20.5 – 46.7% and reduce handover rate by around 59.5 – 78.2% as compared with the benchmarks; in the meanwhile, it maintains a great robustness performance against user mobility and channel variation.
Related Topics
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1109/access.2022.3228570
- https://ieeexplore.ieee.org/ielx7/6287639/6514899/09982460.pdf
- OA Status
- gold
- Cited By
- 11
- References
- 31
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4313188131
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4313188131Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1109/access.2022.3228570Digital Object Identifier
- Title
-
An Artificial Neural Network-Based Handover Scheme for Hybrid LiFi NetworksWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2022Year of publication
- Publication date
-
2022-01-01Full publication date if available
- Authors
-
Guanghui Ma, Rajendran Parthiban, Nemai Chandra KarmakarList of authors in order
- Landing page
-
https://doi.org/10.1109/access.2022.3228570Publisher landing page
- PDF URL
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https://ieeexplore.ieee.org/ielx7/6287639/6514899/09982460.pdfDirect link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
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https://ieeexplore.ieee.org/ielx7/6287639/6514899/09982460.pdfDirect OA link when available
- Concepts
-
Handover, Computer science, Computer network, Robustness (evolution), Channel (broadcasting), Wireless, Wireless network, Artificial neural network, Throughput, Real-time computing, Visible light communication, Scheme (mathematics), Transmission (telecommunications), Fidelity, Artificial intelligence, Telecommunications, Optics, Gene, Biochemistry, Physics, Mathematics, Light-emitting diode, Chemistry, Mathematical analysisTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
11Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 6, 2024: 3, 2023: 2Per-year citation counts (last 5 years)
- References (count)
-
31Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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