With the advent of new high data rate wireless applications, as well as growth of existing wireless services, demand for additional bandwidth is rapidly increasing. Existing spectrum allocation policies of the Federal Communications Commission (FCC) prohibits unlicensed access to licensed spectrum, constraining them instead to several heavily populated, interference-prone frequency bands, which causes spectrum scarcity. However, it has been shown by several spectrum measurement campaigns that the current licensed spectrum usage across time and frequency is inefficient. Therefore, a concept of unlicensed users temporarily ``borrowing" spectrum from incumbent license holders to improve the spectrum utilization, called ``spectrum pooling", which is based on dynamic spectrum access (DSA), is proposed. Cognitive radio is a communication paradigm that employs software-defined radio technology in order to perform DSA and offers versatile, powerful and portable wireless transceivers. Orthogonal frequency division multiplexing (OFDM) is a promising candidate for cognitive radio transmission. OFDM supports high data rates that are robust to channel impairments. In addition, some subcarriers can be deactivated which constitutes a non-contiguous OFDM (NC-OFDM) transmission. However, one of the biggest problems for OFDM transmission is high out-of-band (OOB) radiation, which is caused by sinc-type function representing the symbols during one time constant. Thus, high sidelobe may occur that will interfere with neighboring transmissions. This thesis presents two novel techniques for NC-OFDM sidelobe suppression. Another concern about cognitive radio systems is that the influence of frequency-selective fading channel. Consequently, this thesis also presents a combined approach employing power loading, bit allocation and sidelobe suppression for OFDM-based cognitive radio systems optimization.
| Identifer | oai:union.ndltd.org:wpi.edu/oai:digitalcommons.wpi.edu:etd-theses-1673 |
| Date | 03 May 2009 |
| Creators | Yuan, Zhou |
| Contributors | Alexander M. Wyglinski, Advisor, Kaveh Pahlavan, Committee Member, Andrew G. Klein, Committee Member |
| Publisher | Digital WPI |
| Source Sets | Worcester Polytechnic Institute |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Masters Theses (All Theses, All Years) |
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