Physics

AI designs advanced antenna for satellite communications across multiple frequencies

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Machine learningSatellite communic…

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This study presents a machine learning-assisted design for a four-port Multiple-Input Multiple-Output (MIMO) antenna system operating across C-band (4-8 GHz), X-band (8-12 GHz), and Ku-band (12-18 GHz) frequencies for satellite communications. The antenna utilizes a coplanar waveguide (CPW) feeding mechanism with integrated slots and a cross-neutralization line to reduce mutual coupling between antenna elements, thereby improving isolation and overall performance. Machine learning algorithms were employed to optimize the antenna's geometric parameters for wideband operation across these three critical satellite frequency bands.


This work addresses a key challenge in modern satellite communication systems by enabling compact, multi-band MIMO antennas with improved signal quality and reduced interference. The ML-assisted design approach could accelerate the development of next-generation satellite terminals and enhance data transmission rates for commercial and military satellite applications.


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Source: ML-assisted wideband CPW-Fed slotted four-port MIMO antenna with cross-neutralization line for C-, X-, and ku-band satellite applications