  Hybrid analog-digital precoding is challenging for broadband millimeter-wave
(mmWave) massive MIMO systems, since the analog precoder is frequency-flat but
the mmWave channels are frequency-selective. In this paper, we propose a
principal component analysis (PCA)-based broadband hybrid precoder/combiner
design, where both the fully-connected array and partially-connected subarray
(including the fixed and adaptive subarrays) are investigated. Specifically, we
first design the hybrid precoder/combiner for fully-connected array and fixed
subarray based on PCA, whereby a low-dimensional frequency-flat
precoder/combiner is acquired based on the optimal high-dimensional
frequency-selective precoder/combiner. Meanwhile, the near-optimality of our
proposed PCA approach is theoretically proven. Moreover, for the adaptive
subarray, a low-complexity shared agglomerative hierarchical clustering
algorithm is proposed to group the antennas for the further improvement of
spectral efficiency (SE) performance. Besides, we theoretically prove that the
proposed antenna grouping algorithm is only determined by the slow time-varying
channel parameters in the large antenna limit. Simulation results demonstrate
the superiority of the proposed solution over state-of-the-art schemes in SE,
energy efficiency (EE), bit-error-rate performance, and the robustness to
time-varying channels. Our work reveals that the EE advantage of adaptive
subarray over fully-connected array is obvious for both active and passive
antennas, but the EE advantage of fixed subarray only holds for passive
antennas.
