Video streaming over cognitive radio networks

We propose a framework for video transmission over cognitive radio networks. Our objective is to determine the optimal streaming policy, optimal enhancement layer bit rate of each frame, in order to maximize the overall perceived video quality while keeping quality fluctuation at minimum. In our framework we introduce a channel usage pattern model based on the two-state Markov model and estimate the future busy and idle duration of spectrum based on past observations. On the basis of this scheme, we formulate the streaming optimization problem under the constraint of the available bandwidth budget so that the optimal number of enhancement layer bits are assigned to each frame. We extend this algorithm for three different optimization levels: frame, GOP and scene. We evaluate our algorithm through extensive trace-driven simulation, and show it improves the received video quality and increases bandwidth utilization.