Wireless Schedulers with Future Sight via Real-Time 3D Environment Mapping

This paper proposes a new wireless scheduling methodology which takes advantage of future predictions of data rate for the several users competing for physical access. Based on a system which allows low-cost 3D mapping of an environment in real-time, the predictions are obtained via either low-resolution path-loss prediction given the physical structure of the surroundings or by reference to data rates achieved by previous visitors to a locality. The proportional fair scheduling (PFS) metric is extended to include measures of the future rates users may achieve, leading to a new family of schedulers. They show useful fairness improvements over PFS in exchange for a small capacity loss, and allow a number of configuration options and a range of trade-offs between fairness and capacity.