Spectrum sensing and resource allocation models for enhanced OFDM based cognitive radio

Multicarrier waveforms have been commonly proposed as strong candidates for cognitive radio (CR) due to their high spectrum efficiency, flexibility in resource allocation and commonality of signal processing for spectrum sensing and spectrum utilization. OFDM based 802.11 Wireless Local Area Network (WLAN) technologies are good candidates as CR waveforms. However, the OFDM based systems have significant limitations as CR due to their limited spectral containment, which degrades the performance in determining the free spaces and in coordinating the spectrum usage. Therefore, methods for suppressing the spectral sidelobes of OFDM are considered in this study. In particular, a combination of edge windowing and cancellation carrier techniques is applied for sidelobe suppression. In this study, such an enhanced OFDM scheme is compared with traditional OFDM and filter bank based schemes in spectrum sensing and spectrum allocation, considering also the spectral leakage effects appearing in practical WLAN devices due to power amplifier nonlinearity.