A Predictive Resource Allocation for Wireless Communications Systems.

Using event-driven computer simulations, we test a predictive resource allocation scheme for broadband wireless communications systems based on the Kalman Filter. We implemented the filter in six different scheduling algorithms and selected the best performing of them (EXP Rule and FLS) for a detailed analysis. We considered several simulation scenarios with velocities ranging from 0 to 350 km/h representing pedestrian, vehicular and high-speed train scenarios. We also considered different traffic profiles by changing the number of mobile devices between 10 and 250. Our simulations showed improvement in throughput, spectral efficiency, and a decrease in packet loss rates for two schedulers: the EXP Rule and the Frame Level Scheduler. Our predictor can be applied to any wireless system that performs centralized resource allocation based on data rate or any other quantity that needs to be estimated for resource distribution in a network.