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A Cross-Layer Design for the Performance Improvement of Real-Time Video Transmission of Secondary Users Over Cognitive Radio Networks

机译:一种跨层设计,用于提高认知无线电网络上辅助用户的实时视频传输的性能

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摘要

Cognitive radio (CR) has been proposed as a promising solution to improve connectivity, self-adaptability, and efficiency of spectrum usage. When used in video applications, user-perceived video quality experienced by secondary users is a very important performance metric to evaluate the effectiveness of CR technologies. However, most of the current research only considers spectrum utilization and effectiveness at medium access control (MAC) and physical layers, ignoring the system performance of the upper layers. Therefore, in this paper, we aim to improve the user experience of secondary users for wireless video services over CR networks. We propose a quality-driven cross-layer optimized system to maximize the expected user-perceived video quality at the receiver end under the constraint of packet delay bound. By formulating network functions such as encoder behavior, cognitive MAC scheduling, transmission, as well as modulation and coding into a distortion-delay optimization framework, important system parameters residing in different network layers are jointly optimized in a systematic way to achieve the best user-perceived video quality for secondary users in CR networks. Furthermore, the proposed problem is formulated into a MIN-MAX problem, and solved by using dynamic programming. The performance enhancement of the proposed system is evaluated through extensive experiments based on H.264/AVC.
机译:认知无线电(CR)已被提出作为一种有前途的解决方案,以提高连接性,自适应性和频谱使用效率。当用于视频应用时,二级用户体验到的用户感知视频质量是评估CR技术有效性的非常重要的性能指标。但是,当前的大多数研究都只考虑了介质访问控制(MAC)和物理层的频谱利用率和有效性,而忽略了上层的系统性能。因此,本文旨在改善CR网络上无线视频服务的二级用户的用户体验。我们提出了一种质量驱动的跨层优化系统,以在数据包延迟限制的约束下最大化接收器端预期的用户感知视频质量。通过将诸如编码器行为,认知MAC调度,传输以及调制和编码之类的网络功能表述为失真延迟优化框架,可以系统地共同优化位于不同网络层的重要系统参数,以实现最佳用户CR网络中二级用户的感知视频质量。此外,将提出的问题公式化为MIN-MAX问题,并使用动态规划解决。通过基于H.264 / AVC的大量实验评估了所提出系统的性能。

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