Optimal adaptive channel scheduling for scalable video broadcasting over MIMO wireless networks

Video broadcasting is an efficient way to deliver video content to multiple receivers. However, due to heterogeneous channel conditions in MIMO wireless networks, it is challenging for video broadcasting to map scalable video layers to proper MIMO transmit antennas to minimize the average overall video transmission distortion. In this paper, we investigate the channel scheduling problem for broadcasting scalable video content over MIMO wireless networks. An adaptive channel scheduling based unequal error protection (UEP) video broadcasting scheme is proposed. In the scheme, video layers are protected unequally by being mapped to appropriate antennas, and the average overall distortion of all receivers is minimized. We formulate this scheme into a non-linear combinatorial optimization problem. It is not practical to solve the problem by an exhaustive search method with heavy computational complexity. Instead, an efficient branch-and-bound based channel scheduling algorithm, named TBCS, is developed. TBCS finds the global optimal solution with much lower complexity. The complexity is further reduced by relaxing the termination condition of TBCS, which produces a (1 − ε)-optimal solution. Experimental results demonstrate both the effectiveness and efficiency of our proposed scheme and algorithm. As compared with some existing channel scheduling methods, TBCS improves the quality of video broadcasting across all receivers significantly.