Quality-optimized downlink scheduling for video streaming applications in LTE networks

As the next generation of all-IP mobile communication system, LTE offers unprecedented data transmission speed and low latency for a variety of applications and services. However efficient QoS provisioning for wireless networks is challenging due to unreliable and resource-constrained radio interface. In this paper, we investigate the important downlink scheduling problem in LTE networks with a focus on video streaming applications. Unlike the conventional scheduling rules which exploit the network layer metrics, our scheme is directly targeted on optimizing the application-layer video quality within the required end-to-end delay bound. The video quality optimized scheduling is formulated as a complex combinatorial optimization problem with an exponentially-growing search space. To solve this complex optimization problem, we exploit the GA (genetic algorithm) based metaheuristic approach. The intrinsic strength of population based solution of GA offers a superior advantage for this type of scheduling problems. Performance of the proposed crosslayer design and the GA solution is evaluated against the well-known M-LWDF scheduling rule and a trajectory method. The simulation results demonstrate the effectiveness of the GA based quality-optimized approach. It can enhance the video quality significantly and satisfy the delay bound.