Mechanisms for resilient video transmission in wireless networks

Abstract

Remote video viewing is largely growing, especially in wireless devices. Therefore, video transmission mechanisms such as retransmission and Forward Error Correction (FEC) are very important to ensure that the video arrives at its destination while retaining its quality. While some of these mechanisms can obtain good performance, this does not mean they provide an optimal situation. There are several factors that negatively impact Quality of Experience (QoE) in video transmission, such as network congestion, loss and type of video being transmitted. Adaptive Forward Error Correction schemes aim at providing protection against loss errors by analysing several relevant characteristics of the video and/or network, and using them to apply unequal error protection (UEP) to di erent parts of the video. Taking this into account, it is clear that an adaptive FEC mechanism is a viable option to achieve optimal error protection, thus increasing the video transmission's resilience against errors and losses, and therefore improving Quality of Experience for the end user. This work presents and examines the state-of-the-art mechanisms for retransmission, FEC, QoE, video classi cation and algorithm optimization. The assessment of the mechanisms presents an in-depth study of each concept and individually explores their advantages and disadvantages. Three mechanisms which provide adaptive FEC are developed in and evaluated in a simulation environment, with motion classi cation, error correction, adaptive redundancy allocation and loss feedback components. The capabilities of the adaptive FEC mechanisms are evaluated through a wireless network environment in order to assess their performance against other methods. The results obtained through the assessed mechanisms showed incremental improvements through each stage of development. They also showed that it is possible to accurately characterize the intensity of motion in video sequences according to their characteristics. Furthermore, the ndings highlight the importance of shielding sequences with higher amounts of motion intensity with greater quantities of redundancy due to david their higher degradation when subjected to error. The mechanisms achieved a considerable reduction in the amount of redundancy used to shield the data being transmitted, particularly the loss prediction mechanism. At the same time, the mechanisms maintained video quality which combined with the overhead reduction results in an overall improvement of QoE ultimately enhancing video transmission in wireless networks.