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

Abstract

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.