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The available unlicensed spectrum is increasingly being used by new wireless technologies, but past measurements show that the licensed spectrum is extremely underutilized. To address this issue, the IEEE 802.22 Working Group is developing a novel wireless air interface standard based on cognitive radios (CRs), i.e. IEEE 802.22 wireless regional area networks (WRANs). Moreover, over the last decade wireless multimedia applications have developed rapidly, raising significant concerns about the quality of service (QoS) of multimedia stream transmissions. In particular, the Joint Video Team (JVT) and ITU-T Video Coding Experts Group (VCEG) jointly proposed Scalable Video Coding (SVC) as the next-generation multimedia compression standard. However, the current IEEE 802.22 WRAN draft does not specify QoS mechanisms for SVC-encoded multimedia stream transmission in CR networks. To resolve this problem, we developed a cross-layer channel allocation algorithm (CLCAA) and a novel media access control (MAC) protocol to work with the algorithm. The CLCAA adapts to the characteristics of multimedia traffic and variations of wireless channels by determining the weighting of source-destination pair, which is determined by the deadlines of SVC-encoded multimedia streams, the queuing delay and channel conditions. The CLCAA then allocates transmission opportunities to source-destination pairs based on their weightings and game theory. We also conducted extensive simulations to demonstrate the efficiency of the CLCAA scheme. The simulation results show that the CLCAA scheme not only guarantees QoS for multimedia traffic but also achieves fairness across different streams.

As the demand for broadband multimedia wireless services is increasing, improving quality of service (QoS) of the widely deployed IEEE 802.11 wireless LANs (WLANs) has become crucial. To support the QoS required by a wide range of applications, the IEEE 802.11 working group has defined a new standard—the IEEE 802.11e. Substantial studies have been performed on traffic scheduling for variable bit rate (VBR) video transport over 802.11e WLANs. However, within those studies, relatively little attention has been devoted to the QoS transmission of real-time live VBR videos. In this paper, we present a novel traffic scheduling algorithm for IEEE 802.11e that aims at achieving high channel utilization while still guaranteeing QoS requirements for real-time live VBR videos. The novel characteristic of this algorithm, compared to published literatures, is that it predicts the bandwidth requirements for future traffic using a novel traffic predictor designed to provide simple yet accurate online prediction. Analyses using real life MPEG video traces indicate that the proposed traffic predictor significantly outperforms previously published technique with respect to the prediction error. The proposed traffic predictor can also be used independently to estimate any MPEG traffic. The performance of the proposed traffic scheduling algorithm is also investigated by comparing several existing scheduling algorithms. Simulation results demonstrate that the proposed traffic scheduling algorithm surpasses other mechanisms in terms of channel utilization, buffer usage, video quality and packet loss rate.

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