A model-based DL method unrolls WMMSE to jointly optimize RIS phase shift compression and beamforming, showing improved sum-rate with fewer control bits than RIS elements.
Reconfigu rable Intelligent Surface Assisted Multi-User Communications: How Many Reflective Elements Do We Need?
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Model-based Deep Learning for Joint RIS Phase Shift Compression and WMMSE Beamforming
A model-based DL method unrolls WMMSE to jointly optimize RIS phase shift compression and beamforming, showing improved sum-rate with fewer control bits than RIS elements.