@inproceedings{e2131524cecb418595fd1be2a94a47e0,
title = "Novel frequency domain cyclic prefix autocorrelation based compressive spectrum sensing for cognitive radio",
abstract = "Cognitive radio (CR) has received increasing attention and is considered an important solution to the spectral crowding problem. The main idea behind CR technology is to utilize the unused spectral resources which are determined to be available for secondary user by effective spectrum sensing techniques. However, CR technology significantly depends on the spectrum sensing techniques which are applied to detect the presence of primary user (PU) signals. This paper focuses on detecting OFDM primaries using novel frequency-domain cyclic prefix (CP) autocorrelation based compressive spectrum sensing algorithms. To counteract the practical wireless channel effects, frequency domain approaches for PU signal detection are developed. The proposed spectrum sensing method eliminates the effects of both noise uncertainty and frequency selective channels. Using the frequency domain autocorrelation approach results in highly increased flexibility, facilitating robust wideband multi-mode, multi-channel sensing with low complexity. It also allows to sense weak PU signals which are partly overlapped by other strong PU or CR transmissions.",
keywords = "Cognitive radio, Energy detector, Frequency selective channel and noise uncertainty, OFDMVCP, Time and/or frequency domain CP autocorrelation based compressive spectrum sensing",
author = "Sener Dikmese and Zobia Ilyas and Paschalis Sofotasios and Markku Renfors and Mikko Valkama",
note = "Funding Information: This work was supported in part by the Academy of Finland under the project no. 251138 and no. 284724, and the Finnish Cultural Foundation. Publisher Copyright: {\textcopyright} 2016 IEEE.; 83rd IEEE Vehicular Technology Conference, VTC Spring 2016 ; Conference date: 15-05-2016 Through 18-05-2016",
year = "2016",
month = jul,
day = "5",
doi = "10.1109/VTCSpring.2016.7504368",
language = "British English",
series = "IEEE Vehicular Technology Conference",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2016 IEEE 83rd Vehicular Technology Conference, VTC Spring 2016 - Proceedings",
address = "United States",
}