Adaptive QoE-driven video transmission over Vehicular Ad-hoc Networks

Abstract

Vehicular Ad-hoc Networks (VANETs) are envisioned to offer support for a large variety of distributed applications that range from alerting drivers to autonomous driving features and video services. The use of video-equipped vehicles, with support for live transmission, unveils the need for an adaptive Quality of Experience (QoE)-driven mechanism to overcome several challenges and provide a good video quality. These challenges can range from the scarce network resources and vehicles movement to the time-varying channel conditions and high error rates. Adaptive Forward Error Correction (FEC) schemes can be tailored to shield the video transmission with QoE assurance. The adaptive QoE-driven and FEC-based mechanism proposed in the paper safeguard real-time video transmissions over high-mobility and error-prone networks, improving both the usage of resources and the user experience. Benefits and footprint are evidenced through experiments and QoE assessments. The results demonstrate that the proposed mechanism is able to outperform both non-adaptive and adaptive competitors.