A Joint Adaptive Approach for On-Demand Scalable Video Streaming over CR Networks

Abstract

In this paper, an adaptive integrated framework is devised to provide continuous video service from a base station to multiple secondary users over a cognitive radio network. A channel allocation algorithm is introduced to adaptively assign the available channels to the secondary users while taking into considerations their buffer occupancies as well as the maximum available bit budget and the deadlines of the video frames. The proposed scheme aims at improving the video quality by increasing the number of received enhancement layers for each transmitted video frame. This is done by jointly adapting the modulation levels and channel coding while benefiting from frames retransmissions, when possible, to guarantee their successful reception when they can still meet their deadlines. The simulation results show that the proposed scheme reacts to the variations in channel conditions as well the dynamics of the playback buffers at the secondary users’ end by representing the transmitted video information at the highest possible bit rates while exploiting the scalability feature of the encoded video frames. This is reflected in the improved perceptual quality as received by the secondary users with uninterrupted playback.