Zero SolarWing: A Net-Zero Solar Wind-Powered UAV-Enabled RIS System for URLLC Services in 6G Compute First Networks

The transition to sixth-generation (6G) networks demands innovative solutions to address the challenges of energy efficiency, ultra-reliable low-latency communications (URLLC), and sustainable network architectures. Recently, Compute First Networking (CFN) has emerged as a transformative paradigm, enabling efficient integration of computation and communication while addressing critical issues such as energy efficiency and system reliability. In response to these imperatives, the integration of net-zero solar wind-powered unmanned aerial vehicle (UAV)-assisted reconfigurable intelligent surface (RIS) with CFN systems emerges as a pivotal solution for enabling URLLC services. This integration not only meets stringent computation requirements but also minimizes environmental impact, paving the way for sustainable and reliable next-generation networks. In addressing this challenge, our proposed solution, named Zero SolarWing, harnesses renewable energy sources, specifically solar and wind power, to sustainably power UAV coupled with RIS technology. This innovative integration not only reduces carbon emissions but also enhances ultra-high reliability. Our approach includes the formulation of a minimization problem aimed at mitigating total decoding error subject to blocklength allocation and UAV positioning. Through comprehensive simulation studies, we demonstrate the convergence and superior performance of our proposed method compared to fixed benchmarks. Lastly, we show feasibility of our approach in achieving a net-zero system where harvested and consumed energies are equivalent as well as attaining optimal UAV positioning to minimize total decoding error.

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Publication Details

Journal
IEEE Transactions on Consumer Electronics
Published
2025-08-01
DOI
https://doi.org/10.1109/tce.2025.3595874
Citations
1
Primary Topic
UAV Applications and Optimization
Type
article
Field-Weighted Citation Impact
4.99
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article

Zero SolarWing: A Net-Zero Solar Wind-Powered UAV-Enabled RIS System for URLLC Services in 6G Compute First Networks

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1 citations
IEEE Transactions on Consumer Electronics
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article

Zero SolarWing: A Net-Zero Solar Wind-Powered UAV-Enabled RIS System for URLLC Services in 6G Compute First Networks

Ali Ranjha, Syed Muhammad Danish, Mostafa Hussien, Gautam Srivastava, Kapal Dev, Muhammad Asif
article en
1 citations

Abstract

The transition to sixth-generation (6G) networks demands innovative solutions to address the challenges of energy efficiency, ultra-reliable low-latency communications (URLLC), and sustainable network architectures. Recently, Compute First Networking (CFN) has emerged as a transformative paradigm, enabling efficient integration of computation and communication while addressing critical issues such as energy efficiency and system reliability. In response to these imperatives, the integration of net-zero solar wind-powered unmanned aerial vehicle (UAV)-assisted reconfigurable intelligent surface (RIS) with CFN systems emerges as a pivotal solution for enabling URLLC services. This integration not only meets stringent computation requirements but also minimizes environmental impact, paving the way for sustainable and reliable next-generation networks. In addressing this challenge, our proposed solution, named Zero SolarWing, harnesses renewable energy sources, specifically solar and wind power, to sustainably power UAV coupled with RIS technology. This innovative integration not only reduces carbon emissions but also enhances ultra-high reliability. Our approach includes the formulation of a minimization problem aimed at mitigating total decoding error subject to blocklength allocation and UAV positioning. Through comprehensive simulation studies, we demonstrate the convergence and superior performance of our proposed method compared to fixed benchmarks. Lastly, we show feasibility of our approach in achieving a net-zero system where harvested and consumed energies are equivalent as well as attaining optimal UAV positioning to minimize total decoding error.

IEEE Transactions on Consumer ElectronicsVol. 71(3)
Munster Technological University (IE), Tongling University (CN), Brandon University (CA), Algoma University (CA), École de Technologie Supérieure (CA)
Affordable and clean energy
Openalex Percentile: Top 5%
UAV Applications and Optimization
4.99
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