SoftCast-based linear video delivery (LVD) schemes have been proposed as an alternative to traditional video transmission schemes in wireless error-prone environments. The end-to-end performance of SoftCast-based schemes have been evaluated in Xiong et al. (2016), where a theoretical model based on the Peak Signal-to-Noise Ratio (PSNR) metric has been proposed. The latter is limited to the use of a Zero-Forcing (ZF) estimator at the receiver side, and does not consider bandwidth restrictions. Nevertheless, bandwidth restrictions are common and necessary in practice, especially when considering the transmission of video content. It is mandatory to take this aspect into consideration as it may drastically influence the received video quality. In this paper, we provide valid and significant extensions of the initial model. In total, three models are introduced taking into account both (1) bandwidth constraints (i.e., data compression applied), (2) the use of a Linear Least Square Error (LLSE) estimator instead of the ZF one as well as (3) the use of the optimal power allocation. We show that regardless of the bandwidth reduction applied, the type of estimator as well as the power allocation used, the end-to-end video quality can be accurately modeled and predicted at the transmitter according to the video content characteristics, the type of estimator used at the receiver and the channel conditions. The validity of these three models is assessed through extensive end-to-end simulations. These new models give solid theoretical guidelines for optimizing and studying the performance of linear video delivery schemes.

已经提出了基于 SoftCast 的线性视频传输 (LVD) 方案作为无线易错环境中传统视频传输方案的替代方案。Xiong 等人已经评估了基于 SoftCast 的方案的端到端性能。(2016)，其中提出了基于峰值信噪比 (PSNR) 度量的理论模型。后者仅限于在接收端使用迫零 (ZF) 估计器，并且不考虑带宽限制。然而，带宽限制在实践中是常见且必要的，尤其是在考虑视频内容的传输时。必须考虑这一方面，因为它可能会极大地影响接收到的视频质量。在本文中，我们提供了初始模型的有效且重要的扩展。总共，即，应用数据压缩），（2）使用线性最小二乘误差（LLSE）估计器代替 ZF 估计器，以及（3）使用最佳功率分配。我们表明，无论应用的带宽减少、估计器的类型以及使用的功率分配如何，都可以根据视频内容特征、估计器的类型在发射机处准确地建模和预测端到端视频质量在接收器和信道条件下使用。这三个模型的有效性是通过广泛的端到端模拟来评估的。这些新模型为优化和研究线性视频传输方案的性能提供了坚实的理论指导。