Adaptive Multicast Streaming of Virtual Reality Content to Mobile Users

Streaming virtual reality (VR) content is becoming increasingly popular. Advances in VR technologies now allow providing users with an immersive experience by live streaming popular events, such as the Super Bowl, in the form of 360-degree videos. Such services are highly interactive and impose substantial load on the network, especially cellular networks with inconsistent link capacities. In this paper, we perform rigorous analysis of 1300 VR head traces and propose a multicast DASH-based tiled streaming solution, including a new tile weighting approach and a rate adaptation algorithm, to be utilized in mobile networks that support multicast such as LTE. Our proposed solution weighs video tiles based on user's viewports, divides users into subgroups based on their channel conditions and tile weights, and determines the bitrate for each tile in each subgroup. Tiles in the viewports of users are assigned the highest bitrate, while other tiles are assigned bitrates proportional to the probability of users changing their viewports to include those tiles. We compare the proposed solution against the closest ones in the literature using simulated LTE networks and show that it substantially outperforms them. For example, it assigns up to 46% higher video bitrates to video tiles in the users' viewports than current approaches which substantially improves the video quality experienced by the users, without increasing the total load imposed on the network.