Lan, Tianxiang (2016) Evaluate and Optimise Wireless Communication Performance for Typical Buildings. MPhil thesis, University of Sheffield.
Abstract
It is predicted that mobile traffic, mainly taking place indoors, will increase up to 1000 times in the next decade. Future smart buildings/cities will be connected through wireless communication systems. High capacity and reliable wireless communications will play a very important role in future smart building/city. In telecommunications, a femtocell is a small, low-power cellular base station, typically designed for use in a home or small business. It allows service providers to extend service coverage indoors or at the cell edge, especially where access would be limited or unavailable. Since its first commercial deployment by Sprint Nextel Corporation in 2008, femtocell has continued to gain momentum with mobile network operators in America, Asia and Europe. Plenty of phone calls are placed indoor, and the technology is now deployed for residential and commercial use. But, so far, it is not well known how the wireless performance is related to building structures and material properties, and the building design process has not taken into consideration of wireless performance, resulting in poor wireless performance in some passive buildings. In this M.Phil. thesis, first, a set of wireless performance metrics is designed to measure the wireless performance in buildings; second, different building models focus on coverage and capacity are simulated and analysed to compare the influences of typical building structures; third, novel ways to improve building wireless performance will be investigated.
Metadata
Supervisors: | Zhang, Jie and Chu, Xiaoli |
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Awarding institution: | University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Electronic and Electrical Engineering (Sheffield) |
Depositing User: | Mr Tianxiang Lan |
Date Deposited: | 01 Nov 2016 10:27 |
Last Modified: | 01 Oct 2017 00:18 |
Open Archives Initiative ID (OAI ID): | oai:etheses.whiterose.ac.uk:15383 |
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