Energy-Efficient Optimization for IRS-Enabled Multiantenna UAV Video Streaming

Unmanned aerial vehicles (UAVs) have emerged as a promising solution for aerial surveillance applications, such as traffic monitoring, disaster management, and infrastructure inspection. However, in urban environments, ground-based obstructions frequently disrupt the Line-of-Sight (LoS) links between the unmanned aerial vehicle (UAV) and ground users (GUs), which leads to significant performance degradation in video streaming transmission. To enhance air-to-ground (A2G) communication quality, intelligent reflecting surfaces (IRSs) can be employed to construct reconfigurable UAV- IRS- GU links. In this article, we present a novel framework that integrates an IRS with a multiantenna UAV to enable high-quality aerial video streaming service for a group of GUs simultaneously. By jointly optimizing the UAV trajectory, operation time, transmit beamforming, and phase shifts, the total energy consumption of the UAV is minimized while satisfying Quality of Service (QoS) requirements for video streaming. The problem is formulated as an intractable nonconvex optimization problem with closely coupled variables. To tackle such a challenge, we propose a two-stage algorithm to obtain a suboptimal solution. The first stage focuses on minimizing the UAV's propulsion energy consumption through path discretization, alternating optimization (AO), and successive convex approximation (SCA) techniques. The second stage focuses on communication energy minimization, achieved through a double-loop iterative algorithm based on the penalty-based block coordinate descent (P-BCD) technique. Simulation results verify the effectiveness of the proposed algorithms and show significant energy savings compared to several baseline schemes.