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

机译:基于随机的速率控制方法用于认知无线电网络中的视频流

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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.
机译:近来,由于认知无线电网络上的视频流的问题面临着多重挑战,因此引起了研究界的关注。这些挑战来自视频内容本身的性质,无线链接的随机性质以及许可的主要频道的间歇可用性。由于上述原因,本文采用了不同的方法来解决这一问题。特别地,所提出的方法依赖于获得用于在任意任意时间间隔内可以在可用的主要用户的信道上传输的数据总量的统计分布的精确闭合形式表达式。通过与蒙特卡洛模拟的比较,验证了所获得表达式的有效性。然后,我们使用此表达式为认知无线电网络上的视频流提出一种简单的低复杂度基于随机的速率控制方法。由于其计算复杂度低,因此所提出的方法可以由任何基站容易地实现。使用SimEvents模拟器通过报告平均缓冲区占用率,峰值信噪比和饥饿间隔来评估所提出方法的性能。这些指标是针对不同的参数设置报告的。

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