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The hybrid beamforming can significantly improve the spectral and energy efficiencies of the millimeter‐wave (mmWave) massive multiple input multiple output (MIMO) systems without obvious performance loss. However, the fundamental limitation of existing hybrid beamforming is that they include high‐resolution analog‐to‐digital converters (ADCs) which consume high power. To overcome this fundamental limitation, in this paper, spectrum and energy efficient mmWave massive MIMO transmission scheme is proposed that jointly optimizes the hybrid combiner and the number of ADC bits. Particularly, the hybrid combiner is presented as a combination of three parts: the analog combiner matrix, the quantization matrix, and the digital baseband matrix which is based on the Kalman filter. Unlike most existing works that rely on sumrate optimization to design the hybrid combiner, in this work, the mean square error (MSE) is chosen as the main performance metric to describe the reliability of the system. Simulations results confirm that the proposed Kalman based hybrid combiner exhibits the best performance in terms of spectral and energy efficiencies compared to minimum mean square error (MMSE) and zero forcing (ZF) receivers. [ABSTRACT FROM AUTHOR]

The hybrid architecture still be the most attractive solution for the analog‐digital beamforming in millimeter wave (mmWave) large‐scale multiple input multiple output (LS‐MIMO) systems, since it provides the best trade‐off between the achievable rate and the power consumption. When maximizing performance metrics, channel knowledge is required to optimally design the hybrid beamforming. The channel estimation (CE) is essential for wideband mmWave LS‐MIMO to substantially enhance data rates, however, is a challenging task. Practically, the antenna number and the bandwidth for such communications are very large. Therefore, the CE scheme should account for the frequency‐dependence of the array response vectors and thereby the beam squint effect. In the first part, this article addresses a structured analysis compressive sensing (CS) for CE in a frequency selective mmWave LS‐MIMO system without neglecting the beam squint effect. Compared to sparse mmWave CE approach that mostly uses on‐grid dictionaries, our proposed approach considers continually distributed angles of arrival and departure. In the second part, we show that the frequency‐selective mmWave MIMO channels share a common sparsity structure within the same subcarrier‐group. Then, we propose a block‐sparsity‐based CS approach that uses the simultaneous orthogonal matching pursuit method to estimate the mmWave channel. Moreover, we prove the partial sparsity structure shared between all the subcarrier‐groups. Hence, we develop our proposed joint subcarrier‐block‐based CE scheme exploiting these two block‐sparsity structures. Numerical results evaluate the performances in terms of normalized mean‐squared error and spectral efficiency to select the most accurate channel estimator with lower overhead. [ABSTRACT FROM AUTHOR]