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NeTS: Small: Sustainable Wireless Communications with Optimal Utilization of Renewable Energy and Storage

$250,000FY2016CSENSF

University Of California-San Diego, La Jolla CA

Investigators

Abstract

The massive increases in wireless devices and data are expected to lead to significant increases in energy consumption and carbon emissions of future wireless networks. The problem will be exacerbated by a growing number of off-grid base stations powered by diesel. This project addresses the sustainability of future wireless networks by significantly reducing the use of electricity and diesel in running wireless base stations, and thereby carbon emissions. While various techniques have been proposed to reduce power consumption of wireless networks, this project will address the challenging problem of efficient and cost-effective use of intermittent renewable power sources like solar and wind power to minimize grid/diesel power consumption while ensuring no adverse impact on user experience. Additionally, the project will demonstrate the feasibility of solar-powered small cells, significantly enhancing wireless connectivity in rural or remote areas, and enable unplanned and rapid deployments in urban areas. The resulting software and testbed will facilitate future research in renewable energy for wireless networks, and a new course on sustainable communications. The PI will work closely with University of California-San Diego Center for Wireless Communications industry members to validate the techniques developed, and facilitate adoption in their products which will lead to adoption of solar and wind energy sources to power future generations of wireless networks. The project will introduce the concept of using data storage in user devices to transfer surplus renewable power to surplus data stored, to be utilized during periods of deficit renewable power to reduce electricity/diesel, with no need for energy storage. It will be enabled by a novel dynamic base station resource allocation technique which can indirectly impact data rate. This, in turn, will affect the data stored at user devices and also the base station power consumed, depending on surplus and deficit periods, without affecting user experience. A second technique will be developed for use of an additional low capacity energy storage at the base station to further enhance utilization of the temporally varying renewable power. The technique will simultaneously decide to use project will also develop new dynamic user association and transmit power adaptation techniques making use of spatial variations in renewable power between neighboring base stations to minimize total grid electricity/diesel consumed for heterogeneous networks, including showing feasibility of solar-only powered small cells. A simulation framework and testbed will be developed to demonstrate the effectiveness of the approaches.

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