Efficient Dual-Hop Massive MIMO IoT Networks with UAV DF Relaying and Hybrid Beamforming

This study considers a dual-hop massive multiple-input multiple-output (mMIMO) system, where a decode-and-forward (DF) relay in the form of an unmanned aerial vehicle (UAV) facilitates the transmission of multiple data streams from a base station (BS) to a gateway serving multiple Internet-of-Things (IoT) devices. To maximize the end-to-end throughput in a three-node wireless sensor network (WSN), we investigate a novel joint optimization problem of hybrid beamforming (HBF) and UAV relay positioning in a given deployment span. The study adopts a geometry-based millimeter-wave (mmWave) channel model for both links and utilizes particle swarm optimization (PSO) to optimize the UAV location. The radio frequency (RF) stage is designed to minimize the number of RF chains through the utilization of slow time-varying angular information, while the baseband (BB) stage is designed through singular value decomposition (SVD) of the reduced-dimension effective channel matrix. The illustrative results show that the proposed joint HBF approach enhances energy efficiency compared to full-digital beamforming, and the UAV DF relay, placed via the PSO-based deployment scheme, attains a higher capacity compared to fixed UAV deployment locations.