Adaptive motion-aware FEC-based mechanism to ensure video transmission

Video transmission over wireless networks has shown a great increase in recent years and it is becoming part of our daily life. Meanwhile, several difficulties can impair the success of the transmission, such as limited network resources, high error rates and fluctuating signal strength that may lead to variable bandwidth. Therefore there is the need for adaptive mechanisms that can provide a good video transmission. Adaptive Forward Error Correction (FEC) techniques which assure Quality of Experience (QoE) are a convenient means of delivering video data to wireless users in dynamic and error prone networks, while taking into account the content of the transmitted data. This paper proposes an adaptive content-aware and Random Neural Network (RNN) based mechanism to provide protection of real-time video streams against packet loss in wireless networks, improving user experience and optimising network resources. The benefits of the proposed mechanism are demonstrated through simulations and assessed with QoE metrics.