Cost-effective hybrid precoding has been attracting extensive attention for millimeter wave full-dimension multiple input multiple output (FD-MIMO) green communication systems. To enhance beamforming flexibility and energy efficiency (EE) while obtaining satisfactory spectral efficiency (SE), this paper introduces an adaptive fully-connected subarrays structure with two-layer shared phase shifters (TPSAS) and proposes a TPSAS-based two-stage double dimensional hybrid precoding (TSDDHP) algorithm. Firstly, the TPSAS structure is given to reduce hardware complexity while attractively making full use of the vertical and horizontal dimensions information. Then, to achieve TPSAS-based energy-efficient and flexible hybrid precoding, the TSDDHP algorithm is developed to obtain digital and analog precoders for point-to-point (PTP) and multi-user (MU) scenarios. For PTP scenario, the vertical analog precoder, the horizontal analog precoder, and the digital precoder are acquired by the equivalent quadratic function, properties of dual norm and unitarily invariant norm, respectively. For MU scenario, a linear zero-forcing approach and an equivalent quadratic function are used to gain the digital, the vertical and horizontal analog precoders, respectively. Theoretical analyses and simulation results verify that the proposed scheme is superior to others in terms of beamforming flexibility and EE while acquiring satisfactory SE with lower computation complexity.

As one of the promising technologies for the forthcoming 6G millimeter-wave massive multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) systems, hybrid precoding/combining can achieve trade-off between the achievable rate, the power consumption, and cost. In this paper, a two-stage joint hybrid precoding/combining algorithm based on masterful row and column selection (MCUR) decomposition is proposed for the MIMO-OFDM system with subsystems, named as MCUR-TS. During the first stage, the analog precoder/combiner are found by the MCUR and viewpoint of subsystems, which includes the analog precoding/combining subsystems. Then, using the MCUR and notion of equivalent channel, the digital precoder/combiner are acquired. Different from the existing singular value decomposition (SVD)-based algorithms, the proposed MCUR-based algorithm preserves the sparsity of original data while reducing the computational complexity. Meanwhile, the MCUR with the truncated rotated orthogonal triangular factorization and the gravity centers of column subspaces enhances the performance of hybrid precoding/combining. Furthermore, the phase shifter quantization and imperfect channel state information are applied to decrease energy consumption and improve practicality, respectively. Extensive simulations and theoretical analyses illustrate that the proposed algorithm outperforms other methods in terms of spectral efficiency and achievable sum rate with lower complexity while providing with better robustness to channel errors.