Quality-Driven Beamforming Design for IRS-Aided Video Broadcasting

Broadcasting is an essential service for video transmission, particularly when wide distribution of common content is required. However, providing high-performance broadcasting service remains a crucial challenge when users are located in areas with poor channel quality and the transmit power budget is insufficient. To address such difficulty, intelligent reflecting surfaces (IRSs) can be employed to construct reconfigurable BS-IRS-user links, thereby enhancing spectral and power efficiency. In this paper, we design a quality-driven video broadcasting framework assisted by the IRS. The problem is formulated as the maximization of the minimum peak signal-to-noise ratio (PSNR) for all users via a joint optimization of active and passive beamforming. To address the formulated non-convex problem, we introduce an effective algorithm that leverages penalty-based successive convex approximation (P-SCA) to achieve a suboptimal solution. Simulation results validate the efficiency of the proposed algorithm and unveil the impact of video spatial-temporal content complexity on PSNR.