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RF Energy Harvesting for Zero-Energy Devices and Reconfigurable Intelligent Surfaces

Time: Wed 2024-03-06 13.00

Location: Ka-Sal B (Peter Weissglas), Kistagången 16, Kista

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Subject area: Information and Communication Technology

Doctoral student: Morteza Tavana , Kommunikationssystem, CoS

Opponent: Associate Professor George Alexandropoulos, National and Kapodistrian University of Athens, Athens, Greece

Supervisor: Professor Emil Björnson, Kommunikationssystem, CoS; Professor Emeriti Jens Zander, Kommunikationssystem, CoS

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QC 20240214


The growth of Internet of Things (IoT) networks has made battery replacement in IoT devices increasingly challenging. This issue is particularly pronounced in scenarios with a large number of IoT devices, in locations where IoT devices are difficult to access, or when frequent replacement is necessary. The risk of losing or forgetting some IoT devices also exists, leading to a risk of hazardous chemical leakage and e-waste in nature. Radio Frequency(RF) wireless power transfer (WPT) offers an alternative solution for powering these devices. Moreover, it has been observed that the receivers absorb less than one-millionth of the transmitter energy while surrounding objects absorb the remainder. This situation opens up the possibility of leveraging existing wireless infrastructures, such as base stations (BSs), to charge IoT devices. In this thesis, we focus on analyzing the feasibility and limitations of battery-less operation of IoT devices using RF WPT technology, along with energy harvesting (EH) from existing wireless communication infrastructure. We explore both indoor and outdoor scenarios for powering IoT devices. Initially, we consider an outdoor environment where an IoT device periodically harvests energy from existing BSs and transmits a data packet related to sensor measurement. We analyze the coverage range of energy harvesting from a BS for powering IoT devices, which shows a tradeoff between the coverage range and the rate of sensor measurements. Additionally, we compare the operational domain in terms of the range and measurement rate for WPT and battery-powered technologies. Furthermore, we consider the coverage probability for a multi-site scenario, which is the likelihood that a randomly allocated IoT device harvests enough power to enable its operation. We derive an expression for this probability at a random location in terms of harvesting sufficient power for IoT device operation at a given measurement rate. Next, we consider the remote powering of IoT devices inside an aircraft. Wired sensors add weight and maintenance costs to the aircraft. Although replacing data cables with wireless communication reduces costs and simplifies deployment, providing power cables for the sensors remains challenging. We assume fixed locations for IoT devices inside an aircraft. The goal is to minimize the number of WPT transmitters for a given cabin geometry and IoT device duty cycles. We address WPT system design under channel uncertainties through robust optimization. Following this, we turn our attention to energy harvesting at a reconfigurable intelligent surface (RIS). The potential benefits of using RIS compared to traditional relays when it comes to improving wireless coverage have been debated in previous works, under the assumption that both technologies have a wired power supply. The comparison would be entirely different if the RIS can become self-sustaining, which is not possible for relays. Therefore, we explore energy harvesting for RIS, proposing an algorithm for phase adjustment to maximize energy harvesting from RF sources based on power measurements. Lastly, we explore the charging of zero-energy devices (ZEDs) via a RIS. Mitigating the path loss in WPT requires large antenna arrays, which leads to increased hardware complexity, as it demands an RF chain per antenna element. Alternatively, RIS offers high beamforming gain with simpler hardware. Therefore, we consider RIS-assisted RF charging of ZEDs. We develop dynamic algorithms for battery-aware and queue-aware scenarios, adjusting RIS phases and transmission power to meet the requirements.