In this letter, we study the dynamic antenna grouping and the hybrid beamforming for high altitude platform (HAP) massive multiple-input multiple-output (MIMO) systems. We first exploit the fact that the ergodic sum rate is only related to statistical channel state information (SCSI) in the large-scale array regime, and then we utilize it to perform the dynamic antenna grouping and design the RF beamformer. By applying the Gershgorin Circle Theorem, the dynamic antenna grouping is realized based on the novel statistical distance metric instead of the value of the instantaneous channels. The RF beamformer is designed according to the singular value decomposition of the statistical correlation matrix according to the obtained dynamic antenna group. Dynamic subarrays mean each RF chain is linked with a dynamic antenna sub-set. The baseband beamformer is derived by utilizing the zero forcing (ZF). Numerical results demonstrate the performance enhancement of our proposed dynamic hybrid precoding (DHP) algorithm.

This letter proposes an adaptive scheme that switches between cooperative and non-cooperative transmission for multicell downlink systems in Kronecker spatially correlated channels, which exploits statistical channel state information (CSI). Based on the received signal-to-noise ratios (SNRs) and a cooperation metric, we propose a simple base station (BS) association method and then derive low-SNR capacity approximations for both cooperative and non-cooperative systems. Using the results, we provide a low-complexity efficient cooperation switching method to enhance the system capacity. Results show that the proposed method is more efficient than the conventional method to search the switching point.