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Hybrid Beamforming for MISO System via Convolutional Neural Network
2022
Electronics
Hybrid beamforming (HBF) is a promising approach to obtain a better balance between hardware complexity and system performance in massive MIMO communication systems. However, the HBF optimization problem is a challenging task due to its nonconvex property in terms of design complexity and spectral efficiency (SE) performance. In this work, a low-complexity convolutional neural network (CNN)-based HBF algorithm is proposed to solve the SE maximization problem under the constant modulus
doi:10.3390/electronics11142213
fatcat:y2xxlvvfijeyvengc3w3hrcfqy