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THE 2017 WAGS/PROQUEST INNOVATION IN TECHNOLOGY AWARD WINNER:

Vamsi Talla, University of Washington

Power, Communication and Sensing Solutions for Energy Constrained Platforms

We live in a world where mobile devices such as smartphones, smart watches and tablets are commonplace. With rapid strides in technology, we have come a long way from the first main frame computer ENIAC, which occupied 167m2 and consumed 150 kW of electricity. But, we cannot stand still. We are still ways off from the vision of ubiquitous computing where, devices permeate our surroundings and function perpetually, without the need for maintenance or any user interference. Our current devices are either tethered to power cords or use batteries which require constant supervision and maintenance.

In this work we introduce power, communication and sensing technologies to help us achieve the vision of ubiquitous computing. We note that batteries are too restricting for a large number of applications. First, we present RF energy harvesting solutions to replace batteries with power harvested from ambient RF signals. We show that we can use ambient TV and RFID signals to power computing and sensing devices. Next we show that we can transform a Wi-Fi router, a ubiquitous part of the wireless infrastructure into a source of far field wireless power, but without significantly compromising the performance of the Wi-Fi communication.

For communication, we observe that traditional radio based communication is extremely power hungry which limits the lifespan of the device and makes energy harvesting impractical. We show that, using backscatter communication techniques, we can leverage ambient RF signals such as TV and RFID for power and communication between battery-free devices. This enables ubiquitous communication where devices can communicate among themselves at unprecedented scales and in locations that were previously inaccessible. Next, to bring the benefits of backscatter communication to mainstream applications, we demonstrate that using backscatter, we can synthesize Wi-Fi packets at 3–4 orders of magnitude lower power than Wi-Fi radios. These Wi-Fi transmissions at 1-11 Mbps data rate can be received on standard Wi-Fi radios, bringing low power connectivity to the Wi-Fi space.

Finally, we demonstrate that backscatter techniques can also be applied to sensing to reduce power consumption. We use analog backscatter to directly transmit sensor information to a reader at zero power and combine this technique with digital backscatter to develop a digital addressable battery-free microphone.

We believe the technologies developed in this work will bring up a step closer to a world where we are surrounded by perpetually operating devices.

THE 2017 WAGS/PROQUEST HUMANITIES, SOCIAL SCIENCES, EDUCATION AND BUSINESS AWARD WINNER:

Daniela Navia, University of Calgary

Power, Communication and Sensing Solutions for Energy Constrained Platforms

In this thesis I examine how settler colonialism shapes child welfare (dis)placements. I use the term (dis)placement as a point of departure to understand the historical connection between the child welfare and residential school systems. Indigenous youth collaborators, who recently exited the child welfare system, contributed to this research through arts and storytelling. Their verbal and artistic testimonies attest to the degree that child welfare is part of larger historical and political processes including dispossession of land and resources, assimilation of Indigenous peoples, gendered violence, and violent indifference. I argue that youth resistance to dominant systems takes a distinct urban form and is a means of their survival that carries strong potential for change. This thesis highlights the value of a collaborative research praxis and contributes to broader debates on how Indigenous people experience colonialism and continuously create opportunities for transformation.

THE 2017 WAGS/PROQUEST BIOLOGICAL SCIENCES, MATHEMATICS, AND PHYSICAL SCIENCES, LIFE SCIENCES, AND ENGINEERING AWARD WINNER:

Michael Himmelfarb, University of Calgary

Measurement of Amplifier and Mixer Noise Parameters

The work completed in this thesis expands the theory of measuring noise parameter in linear and non-linear devices. A new method is proposed that defines the possible impedance regions that are guaranteed to produce linearly independent system of equations required for accurate noise parameter extraction. The results show the proposed regions produce noise parameter solutions within 3 σ uncertainties of noise parameters found with patterns previously reported in literature but with the minimum of only four impedances. Additionally, a model to characterize the non-linear noise of a Gilbert Cell mixer in terms of multiple sets of noise parameters was successfully implemented using a system of nonlinear equations. A measurement procedure was designed to extract the parameters in the non-linear model in order to solve for the multiple sets of noise parameters. The maximum error between measured and modeled noise factors was less than 3% at any impedance.