Newton Raphson based optimizer for optimal integration of FAS and RIS in wireless systems
In modern wireless networks, the integration of Reconfigurable Intelligent Surface (RIS) and Fluid Antenna System (FAS) technologies offers a promising solution to the critical challenges such as signal attenuation, interference management, and security enhancement. This paper presents an applicatio...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-03-01
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| Series: | Results in Engineering |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2590123024020656 |
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| Summary: | In modern wireless networks, the integration of Reconfigurable Intelligent Surface (RIS) and Fluid Antenna System (FAS) technologies offers a promising solution to the critical challenges such as signal attenuation, interference management, and security enhancement. This paper presents an application of a novel population-based metaheuristic algorithm of Newton Raphson Based Optimizer (NRBO) to efficiently integrating of FAS and RISs in wireless systems. The designed NRBO combines gradient-based search with adaptive population dynamics and leverages the Newton-Raphson Search Rule (NRSR) and Trap Avoidance Strategy (TAS) to balance exploration and exploitation, ensuring faster convergence and avoiding local optima. NRBO dynamically configures RIS elements and fluid-based antennas, adapting to environmental changes and specific communication requirements to enhance wireless performance. Multiple objective models are designed and addressed using the NRBO: maximizing the average attainable rate for each participant, minimizing the average number of FAS in all Users, and jointly optimizing both objectives with weighted considerations. Simulation results show that the NRBO successfully save 62.5% of the FAS ports to be utilized in the jointly optimized model of both objectives. Also, it achieves more saving with 72.9% when considering minimizing the average number of FAS in all Users as a single objective. |
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| ISSN: | 2590-1230 |