Model Predictive Control Algorithm for Video Coding and Uplink Delivery in Delay-Critical Applications

Abstract

Emerging applications such as remote car driving, drone control, or distant mobile robot operation impose a very tight constraint on the delay between the acquisition of a video frame by a camera embedded in the operated device and its display at the remote controller. This paper introduces a new frame-level video encoder rate control technique for ultra-low-latency video coding and delivery. A Model Predictive Control approach, exploiting the buffer level at the transmitter and an estimate of the transmission rate, is used to determine the target encoding rate of each video frame to adapt with minimum delay to sudden variations of the transmission channel characteristics. Then, an $R-(QP,D)$ model of the rate $R$ of the current frame to be encoded as a function of its quantization parameter (QP) and of the distortion $D$ of the reference frame is used to get the QP matching the target rate. This QP is then fed to the video coder. The proposed approach is compared to reference algorithms, namely PANDA, FESTIVE, BBA, and BOLA, some of which have been adapted to the considered server-driven low-latency coding and transmission scenario. Simulation results based on 4G bandwidth traces show that the proposed algorithm outperforms the others at different glass-to-glass delay constraints, considering several video quality metrics.