A Novel OFDM Format and a Machine Learning Based Dimming Control for LiFi
This paper proposes a new hybrid orthogonal frequency division multiplexing (OFDM) form termed as DC-biased pulse amplitude modulated optical OFDM (DPO-OFDM) by combining the ideas of the existing DC-biased optical OFDM (DCO-OFDM) and pulse amplitude modulated discrete multitone (PAM-DMT). The analy...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-08-01
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| Series: | Electronics |
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| Online Access: | https://www.mdpi.com/2079-9292/10/17/2103 |
| _version_ | 1797521495533027328 |
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| author | Itisha Nowrin M. Rubaiyat Hossain Mondal Rashed Islam Joarder Kamruzzaman |
| author_facet | Itisha Nowrin M. Rubaiyat Hossain Mondal Rashed Islam Joarder Kamruzzaman |
| author_sort | Itisha Nowrin |
| collection | DOAJ |
| description | This paper proposes a new hybrid orthogonal frequency division multiplexing (OFDM) form termed as DC-biased pulse amplitude modulated optical OFDM (DPO-OFDM) by combining the ideas of the existing DC-biased optical OFDM (DCO-OFDM) and pulse amplitude modulated discrete multitone (PAM-DMT). The analysis indicates that the required DC-bias for DPO-OFDM-based light fidelity (LiFi) depends on the dimming level and the components of the DPO-OFDM. The bit error rate (BER) performance and dimming flexibility of the DPO-OFDM and existing OFDM schemes are evaluated using MATLAB tools. The results show that the proposed DPO-OFDM is power efficient and has a wide dimming range. Furthermore, a switching algorithm is introduced for LiFi, where the individual components of the hybrid OFDM are switched according to a target dimming level. Next, machine learning algorithms are used for the first time to find the appropriate proportions of the hybrid OFDM components. It is shown that polynomial regression of degree 4 can reliably predict the constellation size of the DCO-OFDM component of DPO-OFDM for a given constellation size of PAM-DMT. With the component switching and the machine learning algorithms, DPO-OFDM-based LiFi is power efficient at a wide dimming range. |
| first_indexed | 2024-03-10T08:13:18Z |
| format | Article |
| id | doaj.art-11483062ca334b29a56c27ae4632170e |
| institution | Directory Open Access Journal |
| issn | 2079-9292 |
| language | English |
| last_indexed | 2024-03-10T08:13:18Z |
| publishDate | 2021-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Electronics |
| spelling | doaj.art-11483062ca334b29a56c27ae4632170e2023-11-22T10:29:59ZengMDPI AGElectronics2079-92922021-08-011017210310.3390/electronics10172103A Novel OFDM Format and a Machine Learning Based Dimming Control for LiFiItisha Nowrin0M. Rubaiyat Hossain Mondal1Rashed Islam2Joarder Kamruzzaman3Institute of Information and Communication Technology, Bangladesh University of Engineering and Technology (BUET), Dhaka 1000, BangladeshInstitute of Information and Communication Technology, Bangladesh University of Engineering and Technology (BUET), Dhaka 1000, BangladeshInstitute of Information and Communication Technology, Bangladesh University of Engineering and Technology (BUET), Dhaka 1000, BangladeshSchool of Engineering, Information Technology and Physical Sciences, Federation University, Gippsland Campus, Churchill, VIC 3842, AustraliaThis paper proposes a new hybrid orthogonal frequency division multiplexing (OFDM) form termed as DC-biased pulse amplitude modulated optical OFDM (DPO-OFDM) by combining the ideas of the existing DC-biased optical OFDM (DCO-OFDM) and pulse amplitude modulated discrete multitone (PAM-DMT). The analysis indicates that the required DC-bias for DPO-OFDM-based light fidelity (LiFi) depends on the dimming level and the components of the DPO-OFDM. The bit error rate (BER) performance and dimming flexibility of the DPO-OFDM and existing OFDM schemes are evaluated using MATLAB tools. The results show that the proposed DPO-OFDM is power efficient and has a wide dimming range. Furthermore, a switching algorithm is introduced for LiFi, where the individual components of the hybrid OFDM are switched according to a target dimming level. Next, machine learning algorithms are used for the first time to find the appropriate proportions of the hybrid OFDM components. It is shown that polynomial regression of degree 4 can reliably predict the constellation size of the DCO-OFDM component of DPO-OFDM for a given constellation size of PAM-DMT. With the component switching and the machine learning algorithms, DPO-OFDM-based LiFi is power efficient at a wide dimming range.https://www.mdpi.com/2079-9292/10/17/2103machine learningorthogonal frequency division multiplexingdimminglight fidelityregression |
| spellingShingle | Itisha Nowrin M. Rubaiyat Hossain Mondal Rashed Islam Joarder Kamruzzaman A Novel OFDM Format and a Machine Learning Based Dimming Control for LiFi Electronics machine learning orthogonal frequency division multiplexing dimming light fidelity regression |
| title | A Novel OFDM Format and a Machine Learning Based Dimming Control for LiFi |
| title_full | A Novel OFDM Format and a Machine Learning Based Dimming Control for LiFi |
| title_fullStr | A Novel OFDM Format and a Machine Learning Based Dimming Control for LiFi |
| title_full_unstemmed | A Novel OFDM Format and a Machine Learning Based Dimming Control for LiFi |
| title_short | A Novel OFDM Format and a Machine Learning Based Dimming Control for LiFi |
| title_sort | novel ofdm format and a machine learning based dimming control for lifi |
| topic | machine learning orthogonal frequency division multiplexing dimming light fidelity regression |
| url | https://www.mdpi.com/2079-9292/10/17/2103 |
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