Multimedia quality improvements for next generation networks

Video is foreseen to be dominant in the Internet and Next Generation Networks, due to the increased usage of multimedia applications. The current Internet, and in particular the mobile Internet, was not designed with video requirements in mind and as a consequence, its architecture is very inefficient when handling video traffic. Not only is a policy optimization required, but it is also important to perform such an optimization in the proper manner. Therefore, providing Quality of Experience for such networks is an open issue and hot research area nowadays. Our goal is to investigate the performance of the PHY/ Application cross-layer optimization, for which we developed an analytical model to optimize the number of timeslots needed for a video to be correctly decoded with enhanced quality. The wireless channel is modeled by means of Markov chain, whose state represent different channel qualities. We exploit Crosslayer (PHY/ Application) solution with respect to application layer information about scalable video layers, and taking user channel status for adapting channel rates. This problem gets more crucial when the case of multicast is considered, as the base station needs to harmonize the heterogeneous requirements of all the users and adapt transmission accordingly. Performance is evaluated for various scenarios to investigate, what is the optimum number of time slots needed for the base layer of SVC, how does the feedback impacts on the end user perceived quality and user satisfaction level, and to what extend is Cross-layer optimization beneficial. Further, we evaluated how the unicast extends to multicast and its impact on end-user goodput, packet delivery delay and quality.