Improving Video QoE in Unmanned Aerial Vehicles Using an Adaptive FEC Mechanism
Unmanned aerial vehicles (UAV) are rising in popularity together with video applications for both military and civilian use. Because of that, it is necessary to address a set of challenges related to the device movement, scarce resources as well as high error rates, making evident the need for an adaptive mechanism to strengthen video transmissions. Adaptive Forward Error Correction (FEC) techniques are known to be suitable to enhance the Quality of Experience (QoE) of video transmitted over error-prone wireless networks with high mobility. This book chapter proposes an adaptive video-aware FEC mechanism that uses motion vectors details to improve real-time UAV video transmissions, providing both higher user experience and better usage of resources. The benefits and drawbacks of the proposed mechanism along with the related work are analysed and put up for test through simulations and evaluated using QoE metrics.
KeywordsMotion Vectors (MV) Forward Error Correction (FEC) Video-aware FEC Fuzzy logic QoE Unequal Error Protection (UEP)
This work was funded by the Brazilian National Counsel of Technological and Scientific Development (CNPq) and also supported by the Intelligent Computing in the Internet of Services (iCIS) project (CENTRO-07-ST24-FEDER-002003), co-financed by QREN, in the scope of the Mais Centro Program.
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