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

Principal Component Analysis Based Broadband Hybrid Precoding for Millimeter-Wave Massive MIMO Systems