Scheduling Delay-Constrained Data in Wireless Data Networks

In modern cellular networks, the channel quality is dynamic among users and also over time. The time-granularity for such dynamics is significantly diverse - either slow or fast compared to packet transmission time. Because of these issues most existing scheduling policies can not work consistently well. In this work, we propose a scheduling policy with performance relatively insensitive to the time-granularity of the dynamics of channel quality. Our policy is self-adaptive to the scale of channel variations by using an ensemble of proposed algorithms. The proposed scheduling policy is proved to have a worst-case performance bound in the existence of both slow and fast time-varying channels. Simulation results confirm that the policy better tolerates channel variations than other popular schemes such as EDF and the Greedy algorithm.