Efficient Trainable Least Squares Approach for PAPR Reduction in OFDM-based Hybrid Beamforming Systems
A trainable least squares approach is proposed to efficiently reduce the peak-to-average power ratio (PAPR) of OFDM signals in hybrid beamforming systems, which have limited bandwidth and digital subspace compared to fully digital beamforming.