Power Line Communication (PLC) based WiFi extenders can improve WiFi coverage in homes and enterprises. Unlike in traditional WiFi networks which use an underlying high data rate Ethernet backhaul, a PLC backhaul may not support high data rates. Specifically, our measurements show that the end-to-end throughput for the concatenated PLC-WiFi link is determined by the bottleneck segment of the aggregated WiFi-PLC link.

The main objective of this dissertation is to maximize the aggregate of WiFi-PLC networks. The main challenge we address is that PLC capacity could be of a lower capacity than the WiFi link. Thus, users that are connected via a good WiFi link could suffer from the poor PLC link associated with the PLC extender they are attached to. Therefore, we develop WOLT, a system that connects each user to a signal extender for the sake of maximizing the aggregate throughput. It does so while accounting for the PLC link capacities and the users' WiFi link qualities. The results obtained from real testbed experiments and high-fidelity simulations and they show that WOLT is capable of increasing the aggregate throughput by more than 2.5x compared to a greedy user association baseline.

Moreover, users that are occluded from the main router could suffer from well-known WiFi impairments such as deep fading and shadowing. To overcome this issue, Distributed Antenna Systems (DAS) have been shown to improve the robustness and stability of the WiFi link. We approach this problem by two solutions. First, we develop PLC-DAS, a system that finds the correct DAS set of extenders for each user in home settings. We compare PLC-DAS against three baselines and across three fairness models. The results from our simulations show an improvement up to 4.5x compared to blindly using all WiFi-PLC extenders to form a DAS transmitter, while maintaining a fairness Jain’s index value of at least 0.97 with proportional and max-min fairness models.

Secondly, we develop Priza, a scalable system that clusters WiFi-PLC extenders into cells and assigns frequencies to each cell. Priza is evaluated via real testbed experiments and high-fidelity simulations and it can increase the aggregate throughput by more than 3x compared to the baseline that creates as large DAS cells as possible.