# Error Resilient Coding Techniques for Video Delivery over Vehicular Networks
## 1 Introduction  
Video delivery over vehicular networks is a challenging task. On the one hand, video streaming requires high bandwidth and timely delivery, and, on the other hand, vehicular networks are error-prone environments with many challenges to deal with (changing topology, high relative speed of nodes, interferences, Doppler effect, etc.). Vehicular Ad-hoc NETworks (VANETs) are a subtype of Mobile Ad-hoc NETworks (MANETs), where the mobile nodes (vehicles) have certain restrictions regarding their mobility (maximum speed, constrained mobility, etc.). In [1], we can find a classification of VANET applications in four categories: (a) active safety; (b) public service; (c) improved driving; and (d) business and entertainment. Examples of video applications can be found in all these categories, such as, emergency video calls (active safety), video surveillance (public services), traffic jam visualization (improved driving), and contextual advertising and tourist information (business and entertainment). Some of the video applications in VANETs may also be provided by other types of networks, like 4G and the future 5G technologies. However, these networks are not always a suitable option, in particular for those application with strict requirements (real-time) or when there is nofixed infrastructure available (remote areas). As an example, a real-time video-assisted overtaking application may require car-to-car direct communication, featuring very low delay and jitter values, a very high level of reliability, being always available even in areas without cellular network coverage. In order to provide error resilient video communications in VANET scenarios, we propose a combination of two different approaches. The first one improves bit stream error resilience at source coding level, i.e., adapting and adjusting video encoding in such a way that the encoded bit stream may provide, up to certain data loss degree, good video quality to the user. For this task we have proposed (a) a new frame partition scheme (a mix of tiles and slices), and (b) seven intra-refresh encoding modes (ranging from low to high intra-refresh rates). In order to enhance the video protection, the second approach proposes the use of well known Forward Error Correction (FEC) techniques to minimize the effect of packet losses. The former approach is based on the High Efficiency Video Coding (HEVC) standard [2] features, and, for the latter approach, we have selected RaptorQ codes technology [3]. A great number of experimental tests have been performed to determine the impact of our proposals on the error resilient capabilities of VANET video delivery services. The results from this evaluation study will provide the appropriate parameter tuning of the proposed approaches which show the best error resiliency in each particular case. We have used two different data loss models. The first one is based on a simple probabilistic data loss model and the other one is based in a more realistic and complex model which takes into account all the details involved in a communication between two VANET network nodes, and also the network scenario details (urban traffic models, real-life urban street networks, etc.). After analyzing the results of the experimental tests, we come to the following conclusions: (a) it is much better to use realistic network models, since results may change with respect to naive models; (b) the use of FEC techniques are highly desirable to guarantee a minimum of video quality, and (c) source coding approaches enhance the resulting video quality in combination with FEC coding. As far as we know, this is the first time that all of these protection tools are proposed and evaluated together in realistic VANET scenarios. The rest of the paper is organized as follows. In Section 2, related work is presented. In Section 3, different source coding techniques are proposed to provide error resilience to the video stream. In Section 4, a channel coding technique based on FEC codes is explained.