UQML Based Precoder Optimization for RSMA-LEO Satellite Networks

초록

In this letter, unsupervised quantum machine learning (UQML) is proposed to optimize linear precoding for rate-splitting multiple access (RSMA) in low earth orbit (LEO) satellite-terrestrial systems. This approach enhances common and private stream transmission from the LEO satellite to a ground station (GS), to address 6G challenges in resource allocation, interference management, and capacity. Simulation results demonstrate significant spectral efficiency gains, indicating UQML's potential for future satellite communication systems.

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