A Stochastic-Based Rate Control Approach for Video Streaming Over Cognitive Radio Networks

Abstract

Recently, the problem of video streaming over cognitive radio networks has attracted the attention of the research community due to the multiple challenges facing it. These challenges stem from the nature of the video content itself, the stochastic nature of wireless links as well as the intermittent availability of the licensed primary channels. Motivated by the above, this paper follows a different approach to tackle such a problem. Specifically, the proposed approach relies on obtaining an exact closed-form expression for the statistical distribution of the total amount of data that can be transmitted over the available primary users’ channels for any arbitrary interval of time. The validity of the obtained expression is verified through a comparison with Monte Carlo simulations. We then use this expression to propose a simple low complexity stochastic-based rate control approach for video streaming over cognitive radio networks. Due to its low computational complexity, the proposed approach can be easily implemented by any base station. The performance of the proposed approach is evaluated using the SimEvents simulator through reporting the average buffer occupancy, the peak signal-to-noise ratio and the inter-starvation interval. These metrics were reported for different parameters settings.