Optimal Bandwidth Allocation for Scalable H.264 Video Transmission Over MIMO Systems

In this paper we propose an optimal strategy for the transmission of scalable video over packet-based multiple-input multiple-output (MIMO) systems. The latest scalable H. 264 codec is used, which provides combined temporal, quality and spatial scalability. In this work, we propose different error concealment schemes to handle packet losses at the decoder. At the encoder we have developed a method for the estimation of the video distortion at the receiver for given channel conditions. We show the performance of our distortion estimation algorithm in comparison with simulated video transmission over wireless channels with packet errors. In the proposed system, we use a MIMO system with orthogonal space-time block codes (O-STBC) that provides spatial diversity and guarantees independent transmission of different symbols within the block code. Rate-compatible turbo codes (RCPT) are used for unequal error protection of the scalable layers. In the proposed constrained bandwidth allocation framework, we use the estimated decoder distortion to optimally select the application layer parameters, i.e. quantization parameter (QP) and group of pictures (GOP) size, and physical layer parameters, i.e. RCPT and symbol constellation. Also, the simulation results show the substantial performance gain by using different symbol constellations across the scalable layers as compared to a fixed constellation