Modelling and Optimising Cognitive Radio Networks

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The last decade has seen unprecedented growth in wireless communication services, which has consequently resulted in severe scarcity of spectrum bands and imposed increasing pressure on the available radio spectrum bands. However, actual frequency usage measurements reported by many researchers indicate some licensed radio spectrums are extremely underutilized. The conventional static spectrum assignment is effective to reduce interference between different wireless services but results in severe spectrum scarcity and low utilization of licensed spectrum. Spectrum sharing is a potential solution to alleviate this dilemma. In response to request from technology companies like Google, Motorola, Microsoft, Earthlink and Dell, to open the unused spectrum known as 'white space' for unlicensed use, the American Federal Communications Commission (FCC) has issued a Notice of Proposed Rule Making advancing cognitive radio (CR) technology as a candidate to implement spectrum sharing. Cognitive radios are radio systems that continuously sense spectrum to identify spectrum white space, and then operate in spectrums whenever the licensed users 'primary users' are not active. In order for a CR node to access certain licensed spectrum without affecting the licensed users, the CR user must accurately detect unused spectrum, select the best available channel to access, and coordinate access to this channel among CR users. The CR users that are operating in licensed spectrum must keep sensing the spectrum and immediately release the channel once a primary user is detected. These requirements make CR network design extremely challenging. The goal of the proposed research is to study CR network modeling and design in order to improve spectrum detection and optimize spectrum sharing. Completion of the proposed research will greatly improve the utilization of licensed spectrum bands and alleviate the pressing spectrum scarcity. The main findings will be patented and licensed to industries. Furthermore, this project will help building Canada research capacity by training additional Highly Qualified Personnel (HQF).