DDPG-Based Optimization for Zero-Forcing Transmission in UAV-Relay Massive MIMO Networks

This study explores the advantages of employing an unmanned aerial vehicle (UAV) in a massive multiple-input multiple-output (MIMO) network with zero-forcing processing at the base station (BS). Considering potential inaccuracies in channel estimation, we derive a closed-form expression for lower bounds on spectral efficiency in the massive MIMO system, utilizing the UAV as an aerial relay. Subsequently, we formulate a comprehensive optimization problem that encompasses UAV placement and user power allocation in the downlink network, aiming to maximize the data rate for terrestrial users. To address the optimization problem, we propose a novel deep learning-based algorithm that jointly optimizes UAV positioning and power allocation. Finally, we present numerical results that not only validate our theoretical framework and but also demonstrates the effectiveness of the proposed approach.