Energy-Efficient Hybrid Beamforming Based on Quantization-Aware Matrix Composition for Massive MIMO Millimeter Waves

Fully digital (FD) beamforming strategies become prohibitive in massive multiple-input multiple-output (mMIMO) systems due to their hardware complexity. Therefore, hybrid digital-analog beamforming (HB) is considered in millimeter waves (mmWaves) to reduce the number of radio frequency (RF) chains. When the analog stage is implemented with low-resolution phase shifters (PSs), which implies quantized phase constraints, the spectral efficiency (SE) is severely affected. To overcome this degradation, the reported designs in the literature improve performance at the cost of adding more RF chains than data streams. However, this solution reduces the energy-efficiency of the system. This work proposes a novel HB method to achieve a near-optimal FD performance for mMIMO systems with the minimum required number of RF chains. The reduction of RF chains arises as a key procedure to obtain an energy-efficient design. The proposed HB scheme is based on a quantization-aware matrix composition (QMC) to systematically compensate for the residual quantization errors. Furthermore, a quantization strategy, called sum Euclidean quantization (SEQ), is introduced to improve the accuracy of the analog stage. Numerical results reveal that unlike previous reported HB methods, a near-optimal SE can be achieved with our proposal while minimizing the number of RF chains and thus, the hardware cost and power consumption.