Multichannel Cognitive Cross Layer Optimization for Improved Video Transmission

Abstract

Multimedia applications particularly real-time video transmission in wireless networks, envisions end to end user perceived video quality as an important QoS parameter to be achieved. Cognitive Radio promising efficient spectrum utilization combined with Cross layer optimization is seen as a powerful combination to achieve the desired video quality. This study proposes Optimal Channel Sensed Multichannel Cognitive MAC (OCSM-CMAC), a QoS driven cross layer system for the joint optimization of different network parameters along the network protocol stack for the improved video transmission. The primary network activity and wireless propagation dependent channel quality are modeled. Depending on the availability of the primary channel and channel condition as provided by an optimal sensing scheme and the encoder parameter in the application layer, cognitive MAC scheduling and PHY layer modulation and coding for the secondary user are optimized to achieve the required QoS. The simulation of channel and the cognitive user activity is done in MATLAB, while the application video coding is performed by H.264/AVC JM 15.1 codec to obtain the results. The results of the proposed OCSM-CMAC scheme demonstrate that improved PSNR and delay performance is achieved under the optimal channel sensing scheme compared to the random sensing scheme.