An Algorithm for Transmitting VR Video Based on Adaptive Modulation

TL;DR

This paper presents an adaptive modulation algorithm for VR video streaming that optimizes transmission by predicting user viewports, partitioning videos, and efficiently utilizing bandwidth to enhance user experience.

Contribution

It introduces a novel VR streaming strategy combining viewport prediction, convex optimization, and adaptive modulation for improved bandwidth efficiency.

Findings

Outperforms existing VR streaming algorithms in simulations

Enhances bandwidth efficiency through adaptive modulation

Improves user experience by optimizing video quality based on predicted viewports

Abstract

Virtual reality (VR) is making waves around the world recently. However, traditional video streaming is not suitable for VR video because of the huge size and view switch requirements of VR videos. Since the view of each user is limited, it is unnecessary to send the whole 360-degree scene at high quality which can be a heavy burden for the transmission system. Assuming filed-of-view (FoV) of each user can be predicted with high probability, we can divide the video screen into partitions and send those partitions which will appear in FoV at high quality. Hence, we propose an novel strategy for VR video streaming. First, we define a quality-of-experience metric to measure the viewing experience of users and define a channel model to reflect the fluctuation of the wireless channel. Next, we formulate the optimization problem and find its feasible solution by convex optimization. In order to improve bandwidth efficiency, we also add adaptive modulation to this part. Finally, we compare our algorithm with other VR streaming algorithm in the simulation. It turns out that our algorithm outperforms other algorithms.