Quality-Driven Cross Layer Design of Video Transmissions over MIMO Systems

Mobile data traffic has been exponentially increasing during the past years. With the prevalence of video-enabled mobile devices such as smart phones, more than half of the total mobile data traffics are attributed to mobile video traffics. Since wireless resource is limited and video-related applications are bandwidth-consuming, efficiently transmitting videos over wireless networks while providing higher perceptual qualities at the end users become the everlasting endeavors of the service providers. The rapid increasing demands of wireless video streaming services have boosted the developments of video delivery technologies. In the application (APP) layer, more efficient video source coding technologies are designed so that videos with higher qualities can be delivered with less bandwidth consumptions. Among the existing video coding technologies, the scalable video coding (SVC) provides a capability of adapting to various needs or preferences of end users as well as to varying terminal capabilities or network conditions, which makes it an attractive candidate for wireless video streaming applications. In the medium access control (MAC) layer, resource allocation techniques, including rate adaptations and channel selections, are optimized for better wireless resource usages. In the physical (PHY) layer, advanced data transmission schemes such as multi-input multi-output (MIMO) are developed for higher spectral efficiency. To better utilize the advantages of different technologies in different layers, cross-layer design driven by optimizing the end users' perceptral quality is highly required. In this dissertation, methods of quality-driven cross-layer design of video transmissions over MIMO systems are discussed.;First, a near optimal transmit power allocation scheme for delivering SVC-based videos over MIMO systems is discussed. According to the channel state information (CSI) feedbacks, the power of each transmit antennas is adaptively optimized subject to an overall power limit. Therefore, the SVC bit streams with different priorities are transmitted with unequal error protections (UEPs) so that the quality of experience (QoE) at the end user is maximized. Both transmission errors in the PHY layer and video source coding characteristics in the APP layer are jointly considered in this scheme. A near optimal solution is achieved by decomposing the original optimization problem into several convex optimization sub-problems. Detailed algorithms with different complexities and their corresponding theoretical reasonings are provided. The near optimality of the proposed scheme, in terms of measured utilities, is shown by comparing with the exhaustive searched optimal solutions. Simulations with real H.264 SVC video traces demonstrate the effectiveness of the proposed scheme by comparing with other existing schemes in terms of well-accepted video quality assessment methods, such as the peak signal-to-noise ratio (PSNR) and the structural similarity (SSIM) index.;Second, a joint rate and power adaptation scheme for SVC-based video transmissions over MIMO systems is discussed. The ultimate goal of this scheme is to maximize the decoding quality at the receiver side. The rate adaptation includes selecting the best modulation and coding schemes (MCSs), set of spatial channels, number of SVC layers (source coding rates) and their corresponding application layer forward error correction (APP-FEC) coding rates. The power adaptation involves the proper allocation of the power to each antenna in the MIMO system. In most of the existing studies, the bit stream of each particular SVC layer is allocated to one spatial channel and the UEP is achieved by transmitting the more important SVC layers through the spatial channels with higher channel gains. However, in the proposed scheme, the bit stream of each particular SVC layer is distributed to multiple spatial channels so that additional diversity gain can be exploited by applying APP-FEC. The UEP can also be achieved with different APP-FEC coding rate on each video layer. Moreover, transmit power allocation is also effectively and jointly determined to improve the system performance. The effectiveness and favorable performance of the proposed scheme are shown by simulations with H.264 SVC traces of high definition (HD) video clips over MIMO systems.