Downlink Scheduling with Probabilistic Guarantees on Short-Term Average Throughputs

We consider the problem of scheduling multiple transmissions on the downlink of a wireless network with probabilistic guarantees on users´ short-term average throughputs. Many interactive data applications have some degree of a latency requirement, and measure performance by average throughput over a relatively short time interval. We refer to the fraction of time that the transmission rate of a user reaches a predefined rate threshold or higher as tail probability. The problem is formulated as minimizing the total resource cost while meeting users´ respective requirements on the tail probability. We present the necessary and sufficient optimality conditions, and propose an online algorithm which can achieve the optimal resource allocation. Simulation results illustrate the convergence properties of the algorithm, the effect of rate thresholds and tail probability thresholds, and the feasible region of system resources for given performance requirements.