Balancing Fairness and Service Utility in IRS-Assisted Aerial VR Streaming Networks

Aerial virtual reality (VR) streaming offers new possibilities for remote VR experiences in hard-to-reach areas. This paper explores an intelligent reflecting surface (IRS)-assisted aerial VR streaming network aimed to maximize overall service utility by optimizing IRS phase shifts, VR bitrate selection, and communication time allocation while meeting quality of service (QoS) and fairness requirement. Since the formulated problem is non-convex, we decompose it into two subproblems: phase shifts optimization, and bitrate selection and time allocation optimization. We derive a closed-form solution for the phase shifts optimization and employ successive convex approximation (SCA) technique for the latter to handle non-convexity. These subproblems are tackled separately, leading to an effective iterative algorithm for a suboptimal solution. Simulation results illustrate the efficacy of the proposed scheme, and reveal the essential tradeoff between fairness and overall service utility.