Intelligent omni-surfaces with hybrid solar and wind energy harvesting

This paper studies the throughput of intelligent omni-surfaces (IOS) when the source recovers power from the sun and wind to broadcast packets to two users Ut and Ur. Ut and Ur are located in the transmit and reflect spaces of IOS. The recovered power from the sun depends on radiation intensity that has a Gaussian distribution. IOS is an excellent candidate for 6G communications as it offers significant performance enhancement. However, IOS using the wind or the solar powers was not yet studied. The harvesting process is optimised to maximise the throughput. IOS with 64 elements offers 48 dB gain.

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Publication Details

Journal
International Journal of Ad Hoc and Ubiquitous Computing
Published
2024-12-31
DOI
https://doi.org/10.1504/ijahuc.2025.143543
Citations
1
Primary Topic
Smart Parking Systems Research
Type
article
Field-Weighted Citation Impact
0.27
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article

Intelligent omni-surfaces with hybrid solar and wind energy harvesting

Faisal Alanazi
1 citations
International Journal of Ad Hoc and Ubiquitous Computing
Smart Parking Systems Research
0.27
article

Intelligent omni-surfaces with hybrid solar and wind energy harvesting

Faisal Alanazi
article en
1 citations

Abstract

This paper studies the throughput of intelligent omni-surfaces (IOS) when the source recovers power from the sun and wind to broadcast packets to two users Ut and Ur. Ut and Ur are located in the transmit and reflect spaces of IOS. The recovered power from the sun depends on radiation intensity that has a Gaussian distribution. IOS is an excellent candidate for 6G communications as it offers significant performance enhancement. However, IOS using the wind or the solar powers was not yet studied. The harvesting process is optimised to maximise the throughput. IOS with 64 elements offers 48 dB gain.

International Journal of Ad Hoc and Ubiquitous ComputingVol. 48(1)
Prince Sattam Bin Abdulaziz University (SA)
Affordable and clean energy
Openalex Percentile: Top 40%
Smart Parking Systems Research
0.27
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