Optimal resource allocation for Medium Grain Scalable video transmission over MIMO channels

In this paper we investigate an optimal solution for adaptive H.264/SVC video transmission over Multiple-Input Multiple-Output (MIMO) channels.We first write the end-to-end distortion of the H.264/SVC video transmission over a diagonal MIMO channel. The total distortion is expressed following three physical layer parameters: power allocation, modulation spectral efficiency and Error Code Correction (ECC) code rate. Minimizing the total distortion is considered as an optimization problem containing both discrete and continuous variables.We use the Lagrangian method associated with Karush–Kuhn and Tucker conditions to find out the optimal continuous physical layer parameters. Concerting the discrete modulation spectral efficiency and ECC code rate, we exploit information of the MIMO system to remove all suboptimal configurations. Therefore, the optimal power allocation is computed only for a reduced number of discrete configurations.The performance of the proposed solution is evaluated over both statistical and realistic MIMO channels. Results show that the proposed solution performs an optimal resource allocation to achieve the best QoS regardless the channel conditions.

► Framework for MGS H.264/SVC video transmission over MIMO channels.
► Cross-layer optimization for H.264/SVC video transmission MIMO channels.
► End-to-end distortion formulation for scalable video transmission over a diagonal MIMO channel.
► Performing an optimal resource allocation.
► Ensuring a valuable QoS regardless the channel conditions.