Mitigating performance degradation of RIS due to element failures using a genetic algorithm-based sparse array strategy

Yangkun Zhu

doi:10.1016/j.aeue.2025.155770

Mitigating performance degradation of RIS due to element failures using a genetic algorithm-based sparse array strategy

2025-03-01

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DOI：10.1016/j.aeue.2025.155770

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A Genetic Algorithm (GA)-based sparse array strategy is introduced to mitigate the performance degradation of Reconfigurable Intelligent Surfaces (RIS) in satellite communication systems due to reconfigurable element failures in this paper. Such failures hinder real-time adjustment via Field Programmable Gate Array (FPGA), leading to permanent open or short circuit conditions. Modeling the remaining operational elements as sparse array elements and optimizing their states with a GA, a new compensation phase distribution can be obtained. Based on this optimized result, the phase states of the remaining operational elements can be dynamically adjusted using an FPGA, thereby mitigating the degradation in RIS radiation performance. This study systematically analyzes the impact of varying failure rates on RIS performance and evaluates the effects of different beam steering angles at a failure rate of 50 % with identical failed elements. The experimental results show the RIS performance enhancement, with a maximum peak gain improvement of 3.26 dB under varying failure rates and 7.1 dB with different beam steering angles.

Keyword:

Reconfigurable intelligent surface (RIS)

Sparse array technology

Genetic algorithm (GA)

Low earth orbit (LEO) satellite communication

Element failure

Mitigating performance degradation of RIS due to element failures using a genetic algorithm-based sparse array strategy

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