Enhanced adaptive cross-layer scheme for low latency HEVC streaming over Vehicular Ad-hoc Networks (VANETs)
This work addresses the problem of real-time video streaming for vehicular communication applications, but it is incremental as it builds on existing cross-layer and HEVC methods.
The paper tackles the challenge of delivering high-quality HEVC video with low latency over Vehicular Ad-hoc Networks (VANETs) by proposing a low-complexity cross-layer mechanism that assigns packets to MAC layer queues based on video encoding structure and network conditions, resulting in significant improvements in video quality and end-to-end delay compared to the standard EDCA method.
Vehicular communication has become a reality guided by various applications. Among those, high video quality delivery with low latency constraints required by real-time applications constitutes a very challenging task. By dint of its never-before-achieved compression level, the new High-Efficiency Video Coding (HEVC) is very promising for real-time video streaming through Vehicular Ad-hoc Networks (VANET). However, these networks have variable channel quality and limited bandwidth. Therefore, ensuring satisfactory video quality on such networks is a major challenge. In this work, a low complexity cross-layer mechanism is proposed to improve end-to-end performances of HEVC video streaming in VANET under low delay constraints. The idea is to assign to each packet of the transmitted video the most appropriate Access Category (AC) queue on the Medium Access Control (MAC) layer, considering the temporal prediction structure of the video encoding process, the importance of the frame and the state of the network traffic load. Simulation results demonstrate that for different targeted low-delay video communication scenarios, the proposed mechanism offers significant improvements regarding video quality at the reception and end-to-end delay compared to the Enhanced Distributed Channel Access (EDCA) adopted in the 802.11p. Both Quality of Service (QoS) and Quality of Experience (QoE) evaluations have been also carried out to validate the proposed approach.