ABRF: Adaptive BitRate-FEC Joint Control for Real-Time Video Streaming

Adaptive Forward Error Correction (AFEC) algorithms are proposed to achieve efficient Forward Error Correction (FEC) in Real-Time Communication (RTC). However, current AFEC approaches suffer two key limitations. 1) They do not consider the squeezing effect of redundancy on source bitrate while the squeezing usually happens in real RTC applications with limited bandwidth. 2) They estimate the future packet loss simply, ignoring some critical features of packet loss like randomness and multi-pattern. These drawbacks stop them from providing better Quality of Experience (QoE) in RTC services. We propose ABRF, a general QoE-oriented Adaptive BitRate-FEC joint control algorithm. ABRF makes predictions on the network loss pattern in the coming time and jointly calculates the optimal bitrate-FEC decision based on a QoE model for real-time video streaming. Moreover, ABRF is equipped with a fast adaptation method which helps it generalize across diverse network environments. In terms of Video Multi-method Assessment Fusion (VMAF), experimental results tell that ABRF decreases VMAF degradation caused by packet loss by 68%-95% compared with other AFEC algorithms in real-time video streaming in real-world Internet.

Automated summary

This article proposes ABRF, a QoE-oriented adaptive bitrate-FEC joint control algorithm. ABRF predicts the network loss pattern in the future and calculates the optimal bitrate-FEC decision based on a QoE model for real-time video streaming. Moreover, ABRF is equipped with a fast adaptation method to generalize across diverse network environments.