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This work considers a multi-user massive multiple-input multiple-output (MU-mMIMO) Internet-of-Things (IoT) system, where multiple unmanned aerial vehicles (UAVs) operating as decode-and-forward (DF) relays connect the base station (BS) to a large number of IoT devices. To maximize the total achievable rate, we propose a novel joint optimization problem of hybrid beamforming (HBF), multiple UAV relay positioning, and power allocation (PA) to multiple IoT users. The study adopts a geometry-based millimeter-wave (mmWave) channel model for both links and utilizes sequential optimization based on K-means UAV-user association. The radio frequency (RF) stages are designed based on the slow time-varying angular information, while the baseband (BB) stages are designed utilizing the reduced-dimension effective channel matrices. The illustrative results show that multiple UAV-assisted cooperative relaying systems outperform a single UAV system in practical user distributions. Moreover, compared to fixed positions and equal PA of UAVs and BS, the joint optimization of UAV location and PA substantially enhances the total achievable rate.
Mahmood et al. (Wed,) studied this question.