The development of a dual-band, four-port MIMO antenna significantly enhances satellite communication by supporting multiple data streams, making it ideal for Wi-Fi routers, mobile devices, and IoT systems. However, designing of compact and cost-effective antenna design for RF Energy Harvesting environments poses unique challenges, especially in balancing bandwidth, gain, and isolation. Therefore, the present research employed a dual-band four-port MIMO antenna with stub loading to get around these challenges, which is RF optimized for energy harvesting applications, operating between the two recommended frequency ranges of 10.5–14 and 8.5–10 GHz. The performance of the antenna is enhanced using a sparsified kookaburra quaternion edge attention graph network (SKQE-ATGRNet) to model and optimize its characteristics. The design process includes establishing antenna geometry, preparing simulation data, and training the SKQE-ATGRNet, followed by iterative optimization using the kookaburra optimization algorithm (KOA). This approach ensures superior bandwidth, gain, isolation, and energy harvesting efficiency. Implemented using Python and CST MW Studio 2021, the proposed design achieves a 96.5% higher efficiency and a maximum gain of 8 dB higher gain, demonstrating significant improvements over existing designs. Integrating SKQE-ATGRNet and innovative optimization techniques in antenna design shows great promise for high-performance satellite communication and applications for harvesting radiofrequency energy.
Kumar et al. (Sun,) studied this question.
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