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Although the millimeter wave (mmWave) band has great potential to address ever-increasing demands for wireless bandwidth, its intrinsically unique propagation characteristics call for different scheduling strategies in order to minimize performance drops caused by blockages. A promising approach to mitigate the blockage problem is proactive scheduling, which uses blockage predictions to schedule users when they are experiencing good channel conditions. In this paper, we formulate an optimal scheduling problem with fairness constraints that allows us to find a schedule with maximum aggregate rate that achieves approximately the same fairness as the classic proportional fair scheduler. The results show that, for the problem settings studied, up to around 30% increase in aggregate rate compared to classic proportional fair scheduling (PFS) is possible with no decrease in fairness when blockages can be accurately predicted 0.5 seconds in advance. Furthermore, aggregate rate could be doubled compared to PFS if blockages can be accurately predicted 5 seconds in advance. While these results demonstrate the very promising potential of proactive scheduling, we also discuss several future research directions that must be pursued to effectively realize the approach. 

To accommodate increasingly intensive application bandwidth demands, mmWave WLAN at 60 GHz has been identified as a promising technology with the potential to achieve Gbps throughput. However, mmWave performance is highly dependent on the signal's line-of-sight (LoS) condition due to its high penetration loss when obstructed. We study the use of dedicated flat passive reflectors to improve coverage in indoor mmWave WLANs through a reflector placement scheme that accommodates any general indoor scenario with pre-deployed ceiling-mounted access points (APs). The reflector locations are efficiently selected among all available vertical surfaces within the indoor environment. Through simulations, we show that deployment of intelligently placed reflectors can improve LoS coverage by up to 10%, which is more than deploying one additional AP. Results are provided to illustrate how different factors affect coverage and insights about preferred reflector placements are provided.