Cross-Layer Optimization for VR Video Multicast Systems

360-degree videos for Virtual Reality (VR) applications are getting more popular because of their diverse applications. However, VR videos usually need more bandwidth than conventional videos to provide the same quality of experience (QoE). Tiled videos can help save bandwidth by selecting lower quality encoding for the tiles with lower probability of viewing. Dynamic Adaptive Streaming over HTTP (DASH) enables the adaptive rate selection of tiles based on the channel conditions. Multicasting also can help save bandwidth, since many users share the spectrum when they request the same video contents. In this paper, we formulate the utility maximization problem to find which tiles should have which video representations to satisfy the most users in multicasting groups using limited resources. A cross-layer optimization framework, which includes user grouping, resource allocation, and the tile-based rate-selection algorithms, is proposed to maximize the total utility among all users. Simulation results show that the proposed cross-layer optimization framework can achieve a higher utility than the broadcasting solution or existing multicast solutions.