Optimal scalable video transmission over wireless networks
MetadataShow full item record
Many video applications, such as mobile TV, videoconferencing, and on-demand video streaming, have gained increased popularity. However, a key problem of video transmission over the existing wireless networks is the mismatch between the nature of the wireless system conditions and the constant quality requirements, such as bandwidth, and packet loss for video applications. Cross-layer design is a natural approach to deal with the incompatibility problem. This approach aims to efficiently perform cross-layer resource allocation (such as bandwidth and transmission power) by increasing the communication efficiency of multiple network layers. In this dissertation, we consider the problem of scalable video transmission over next-generation multi-antenna multi-carrier wireless systems. We propose different resource allocation optimization strategies between application layer and physical layer of the end-to-end system. The proposed framework is general and flexible. Scalability in the video bitstream is exploited by partitioning and producing multiple layers which cater to wide heterogeneous networks. The scalable extension of H.264/AVC, popularly known as scalable video codec (SVC) that provides a combined temporal, quality and spatial scalability is used in this work for transmission over varied networks. We first develop a low-delay low-complexity method for the estimation of the decoded video distortion at the encoder and propose different error concealment schemes. We consider a bandwidth-constrained video transmission over multiple-input multiple-output (MIMO) system with orthogonal space-time block codes (O-STBC). The O-STBC provides spatial diversity and guarantees independent transmission of different symbols within the block code. The hierarchical nature of SVC and orthogonal structure of O-STBC are exploited to design the cross-layer bandwidth optimization strategy. It involves optimally selecting the application layer and physical parameters based on the estimated distortion. The results exemplify the advantages of keeping various parameters under optimization versus allocating them at a fixed value. We consider the transmission of scalable video over MIMO systems using OFDM technique. We propose another modification to the distortion estimation algorithm based on the importance of temporal and quality scalability. We compare the performance under optimal bandwidth allocation framework. Then, we propose transmission power allocation strategies based on using unequal number of OFDM sub-carriers for different layers of scalable video.