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Contribution à l'amélioration des transmissions vidéo dans les réseaux ad-hoc véhiculaires (VANET)

Abstract : At present, vehicular communications have become a reality guided by various applications. In particular, high-quality video delivery with low latency constraints is required for real-time applications. The new state-of-the-art high-effciency video coding (HEVC) standard is very promising for real-time video streaming in vehicular ad hoc networks (VANET). Nevertheless, these networks have variable channel quality and a limited bandwidth that penalizes the overall performances of end-to-end video transmission. In order to meet these constraints, we proposed in this work to consider both transmission and video encoding parameters through a joint source-channel-protocol coding approach to provide an improvement in video transmission. First, we have shown the interest and the gain brought by the "cross-layer" solutions. Then, we developed two approaches. The first one exploits a "crosslayer" solution between the application layer and the Medium Access Control (MAC) layer while the second exploits the transport layer protocols in the adaptation of the video stream. Regarding the first approach, we have proposed solutions to allocate the frames to the most appropriate Access Category (AC) queue on the MAC layer based on the image importance in the video stream. In another solution, we chose multiple descriptions source coding as an error resilient solution. Thus, the simluation results obtained for different realistic vehicular scenarios demonstrate that the proposed transmission schemes offer significant video quality improvements and end-to-end delay reduction compared to conventional transmission schemes.
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Submitted on : Thursday, October 3, 2019 - 2:07:09 PM
Last modification on : Tuesday, December 8, 2020 - 3:32:06 AM


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  • HAL Id : tel-02304659, version 1



Mohamed Aymen Labiod. Contribution à l'amélioration des transmissions vidéo dans les réseaux ad-hoc véhiculaires (VANET). Traitement du signal et de l'image [eess.SP]. Université de Valenciennes et du Hainaut-Cambresis; Université Badji Mokhtar-Annaba, 2019. Français. ⟨NNT : 2019VALE0023⟩. ⟨tel-02304659⟩



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