GNN-Enabled Deep Unfolding for Precoding in Massive MIMO LEO Satellite Communications
IEEE Wireless Communications and Networking Conference（2025）
Key words
Satellite Communication,Low Earth Orbit,Massive Multiple-input Multiple-output,Neural Network,Computational Efficiency,Communication Systems,Invertible,Limited Power,Taylor Expansion,Minimum Mean Square Error,Graph Neural Networks,Earth Orbit,Minimum Mean Square,Earth Orbit Satellites,6G Networks,High Complexity,Power Consumption,Iterative Algorithm,Trainable Parameters,High Computational Complexity,Array Response Vector,Downlink Transmission,Propagation Delay,Doppler Shift,Signal-to-interference-plus-noise Ratio,Precoder Design,Precoding Vector,First-order Taylor Expansion,System Energy Efficiency,Total Power Consumption
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