Studies On QoS Improvement Of Wireless Video

Wireless video QoS technique is a multidisciplinary topic involving many areas, ranging from video coding, wireless communication, optimization theory to networking architectures, networking management and so on. Considering the guaranteed QoS is difficult to achieve for wireless video delivery, the robustness and optimization resource allocation are investigated in this dissertation to provide better video QoS. By taking full advantage of the technologies in the related application, we have done further study on their shortage of robustness, stability or applicability and proposed some novel processing methods and models to efficiently improve video delivery QoS.Firstly, based on the tradeoff between the power consumption and end to end distortion, we propose an efficient decoding power consumption optimization framework. By exploiting turbo decoding and source priority, an unequal decoding power allocation algorithm is proposed, which results in an excellent tradeoff between video quality and power consumption and yields significant improvement of video quality under constrained power consumption.Secondly, for the efficient utilization of network resources, video traffic prediction is necessary in the real application. A novel model based on H_∞algorithm is proposed for video traffic prediction, which not only overcomes the inherent defects in traditional methods but also does not require a priori knowledge of the noise source statistics. More importantly, the proposed prediction model makes use of H_∞model to improve its robust performance. The quantitative analysis of the video traffic prediction results indicates the model has more accurate prediction, better stability, and higher robustness.Finally, two robust video delivery systems are proposed to improve wireless video QoS, namely, unequal spatial diversity gain transmission system based on LSTBC_OFDM_LDPC and unequal error protection video transmission system based on LDPC. The first proposed system not only significantly improves the system performance by exploiting both the spatial diversity gain of LSTBC and the coding gain of LDPC, but also provides an unequal diversity gain mode to match the source of different prioritized streams to achieve better video transmission performance; The second proposed system, by jointly considering source and channel bit allocation under bandwidth constraints, features an unequal number of channel rate bits assignment to different priority stream. Simulation results demonstrate that the proposed algorithm is more robust compared with those obtained with equal error protect (EEP) technique and can achieve 0.5-3 PSNR gains.