Wireless Power Transfer (WPT) will be a key enabler of Internet-of-Things (IoT) networks that consist of low-power devices that harvest energy from Radio Frequency (RF) signals emitted by base stations or access points. Hence, future networks will likely have both low-power RF-energy harvesting devices as well as legacy users such as laptops. In particular, both devices and users will share the same wireless channel to receive RF energy as well as transmit data.
To ensure they share the spectrum efficiently, this thesis considers resource allo- cation problems in Orthogonal Frequency Division Multiple access (OFDMA) net- works. In particular, it considers sub-band/sub-carrier allocation problems that aim to meet the requirement of low-power devices and legacy users when they co-exist in the same network. Specifically, for low-power devices, developed solutions must en- sure low-power devices receive sufficient energy to collect samples or have sufficient energy to transmit frequently t
Abstract
This paper considers minimizing the time required to collect L bits from each Radio Frequency (RF)-energy harvesting device serviced by a multi-antenna Hybrid Access Point (HAP). We outline a Mixed Integer Non-Linear Program (MINLP) to determine the transmit power allocation of the HAP and devices over multiple time slots. We also outline a Receding Horizon Control (RHC) approach coupled with a Gaussian Mixture Model (GMM) to optimize the transmit power allocation of the HAP. Our results show that the performance of our approach is within 5% of the optimal solution.
Open Access Status