OFDM-Based Cognitive Radio for DSA Networks

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 “command-and-control” spectrum allocations defined by government regulatory agencies, such as federal communications commission (FCC), prohibit unlicensed access to licensed spectrum, constraining them instead to several heavily populated, interference-prone frequency bands. However, it has been shown that the spectrum is not utilized efficiently across time and frequency. Therefore, FCC is currently working on the concept of unlicensed users “borrowing” spectrum from incumbent license holders temporarily to improve the spectrum utilization. This concept is called dynamic spectrum access (DSA). Cognitive radios offer versatile, powerful, and portable wireless transceivers enabling DSA. This dissertation investigates physical layer techniques to enhance a cognitive radio performance. Multi-carrier techniques, such as orthogonal frequency division multiplexing (OFDM), support huge data rates that are robust to channel impairments. However, with a growing demand for spectrum access, it may be difficult for any single transmission to obtain a large contiguous frequency spectrum block in DSA environment. This dissertation proposes a novel non-contiguous OFDM (NC-OFDM) technique, where the implementation achieves high data rates via collective usage of a large number of non-contiguous subcarriers while simultaneously avoiding any interference to the existing transmissions by turning off the subcarriers corresponding to these spectrum bands. Moreover, the performance of the proposed NC-OFDM technique is compared with other multi-carrier technique, such as multi-carrier code division multiple access (MC-CDMA). One of the major drawbacks of an OFDM signal is that it may exhibit large peak-toaverage power ratio (PAPR) values resulting in expensive transceivers. This dissertation presents an extensive overview and taxonomy of the PAPR reduction algorithms proposed in the literature. This dissertation presents five novel techniques for reducing PAPR of an OFDM signal viz., subcarrier phase adjustment algorithm, adaptive-mode PAPR reduction algorithm, subcarrier power adjustment algorithm, variable throughput algorithm, and low correlation phase sequences-based algorithm. Due to the noncontiguous nature of the spectrum in DSA environment, the statistical properties of the PAPR of an NC-OFDM signal are different from that of an OFDM signal. Additionally, the conventional PAPR reduction algorithms need to be carefully chosen and modified to be used for reducing the PAPR of an NC-OFDM signal. This dissertation investigates the statistical properties of the PAPR of an NC-OFDM signal and lay out design requirements for the PAPR reduction algorithms for an NC-OFDM signal. OFDM technique implements fast Fourier transform (FFT) algorithms for modulating and demodulating the OFDM signal. This dissertation proposes an efficient general FFT pruning algorithm for improving the efficiency of the FFT evaluation by reducing the arithmetic operations, when a large number of subcarriers are deactivated. Given that the cognitive radios employing NC-OFDM need to quickly adapt to the changing operating environment, and that the hardware resources of small form factor cognitive radios are limited, such an algorithm would be beneficial.