Towards universal power efficient scheduling in Gaussian channels

In this paper, we propose a framework for designing power efficient schedulers for transmitting bursty traffic sources over Gaussian wireless channels that provides deterministic and statistical guarantees on absolute delays experienced by the source packets. The proposed schedulers compute the transmission rate and power using temporal water-filling techniques without any knowledge of the arrival traffic statistics. The schedulers reduce the average transmission power substantially (55% in some scenarios) for small increases in delay. The framework allows us to design schedulers that artfully tradeoff the performance with the complexity of computing the schedulers. We also introduce an iterative process to compute a lower bound on the transmit power of any scheduler that provides absolute delay guarantees. The utility of having accurate traffic predictors is demonstrated; specifically, we show that a perfect one step predictor achieves near optimal performances for small delay bounds. The proposed schedulers and iterative method of computing the lower bound are also shown to provide statistical guarantees on packet delays.