Future cellular systems must accommodate increasing demand for very high throughput and low latency data services. Massive multiple-input multiple-output (MIMO) approach involving base stations equipped with much larger numbers of antennas than the numbers of users served promises to significantly increase network capacity, while nonorthogonal multi-carrier transmission is expected to dramatically reduce the latency.
The ultimate goal of this project is to detect and localize leaks in pipelines in real time. Hifi Engineering has developed distributed fiber optic sensors. Measurements are obtained at evenly spaced intervals along the pipeline (called channels). This project aims to develop data processing tools to improve leak detection and localization. Many events occur along a pipeline whose effects are registered by sensors (trucks driving by, compressors turning on, leaks). Events are registered in many channels as sounds propagate down the pipeline.
The accurate localization of facial keypoints in static images, and their tracking in video has many potential applications. In this project we will address the problem of fine-grained facial keypoint tracking using multiple images and cameras, possibly including depth cameras. We have identified three potential partners, each of whom focus on applications that require the accurate localization and/or tracking of facial keypoints. In one potential application we are interested in detecting certain congenital syndromes using detailed facial analysis.
A novel transmitter architecture which presents more power efficiency than that of the transmitters being used currently in mobile communication base stations, is proposed in this research project. The result of this research fills the gap between the theoretical idea behind this transmitter structure and its practical usage in cellular network base stations. This transmitter can operate over a wide frequency range and with different mobile communication signal standards very power efficiently while maintaining the quality of the transmitted signal.
Machine-to-machine (M2M) user equipments (UEs), which do not require a direct human interaction for communicating to each other, are predicted to have a large end-user market in the near future with numerous potential applications, such as home automation, patient monitoring, transportation, and smart metering. Currently, machine-type communication (MTC) is in the process of being standardized for long term evolution (LTE) cellular networks in the third generation partnership program (3GPP).
The high prevalence of obstructive sleep apnea (OSA) poses a serious threat to the healthy growth and development of many children. The lack of oxygen during sleep can lead to daytime sleepiness, growth failure, behavioural problems and developmental delay. Polysomnography (PSG), the gold standard to diagnose OSA is high in cost, requires a well-equipped sleep laboratory and overnight stay. The Phone Oximeter, is a mobile device that integrates a pulse oximeter with a cell phone. In addition to the blood oxygen saturation (SpO2), it provides a signal of changes in blood volume.
The proposed project aims at the design and implementation of low complexity digital pre-distortion (DPD) algorithms for multiband and multiple input multiple output (MIMO) wireless transmitters. The power amplifier (PA) is one of the major sources of power dissipation in wireless base stations. The DPD techniques enable the PA to operate in a more efficient power level resulting in more energy efficient wireless networks.
Network stochastic control is considered as a primary goal in the design of emerging wireless networks. One of the objectives in the stochastic control of wireless networks is to enable crosslayer designs to achieve stochastically optimal resource allocation in the physical and MAC layers. Different stochastic performance criteria can be considered in the optimal control of wireless networks. Delay is one of the most challenging ones and has been addressed far less in the literature.
Finite Difference Time Domain (FDTD) simulations allow researchers to model complex devices and systems based on integrated micro/nano structures. The electrodynamic behaviour predicted by FDTD simulations match very well with the real physical systems, which significantly accelerates the development of novel devices. However, there are limitations in existing FDTD techniques to model metal nanoparticles on sub-100 nm length- scales, which are of great interest to research and industry.
Electrochemical reduction of carbon dioxide (ERC) is a process by which carbon dioxide (CO2) is converted into valuable chemical products via chemical reactions driven by electricity. The goal of this project is to fabricate and test catalytic metal electrodes to increase the efficiency of ERC reactors converting carbon dioxide from industrial exhaust gas streams into formic acid.