@article { 11570_3131282,
	title = {GSM-RF Channel Characterization Using a Wideband Subspace Sensing Mechanism for Cognitive Radio Networks},
	journal = {WIRELESS COMMUNICATIONS AND MOBILE COMPUTING},
	volume = {2018},
	year = {2018},
	pages = {1{\textendash}11},
	abstract = {In this paper, we examine a spectrum sharing opportunities over the existing Global System of Mobile Communication (GSM) networks, by identifying the unused channels at a specific time and location. For this purpose, we propose a wideband spectrum sensing mechanism to analyze the status of 51 channels at once, belonging to the 10 MHz bandwidth centered at the frequency 945 MHz, in four different areas. We propose a subspace based spectral estimation mechanism, adapted to deal with real measurements. The process begins with data collection using Secondary User (SU) device enabled with Software Defined Radio (SDR) technology, configured to operate in the GSM band. Obtained samples are used then to feed the sensing mechanism. Spectral analysis is delivered to estimate power density peaks and corresponding frequencies. Decision making phase brings together power thresholding technique and GSM control channel decoding to identify idle and busy channels. Experiments are evaluated using detection and false alarm probabilities emulated via Receiver Operating Characteristic (ROC) curves. Obtained performances show better detection accuracy and robustness against variant noise/fading effects, when using our mechanism compared to Energy Detection (ED) based ones as Welch method, and Beamforming based ones as Minimum Variance Distortionless Response (MVDR) method. Occupancy results exhibit considerable potential of secondary use in GSM based primary network.},
	keywords = {Cognitive Radio Networks, GNU-Radio, GSM, USRP, Wideband Subspace Sensing},
	doi = {10.1155/2018/7095763},
	url = {https://www.hindawi.com/journals/wcmc/2018/7095763/},
	author = {El Barrak, Soumaya and El Gonnouni, Amina and Serrano, Salvatore and Puliafito, Antonio and Lyhyaoui, Abdelouahid}
}
@article { 11570_3115061,
	title = {Implementation of a low cost SDR-based Spectrum Sensing Prototype using USRP and Raspberry Pi board},
	journal = {INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH \& ENGINEERING TECHNOLOGY},
	volume = {20},
	year = {2017},
	pages = {54{\textendash}58},
	abstract = {Our paper presents a low cost experimental prototype for cognitive radio applications, which consists of a radio platform and a host cognitive engine, dedicated essentially to Wireless Sensor Networks (WSN) scenarios. It is carried out using {\textquoteleft}USRP (Universal Software Radio Peripheral) and GNURadio{\textquoteright} Software Defined Radio (SDR) platform, implemented on a single board computer, which is the Raspberry Pi 3 board. We have experienced the Spectrum Sensing mechanism, based upon Energy-Detection approach, due to its low computational complexity, and implementation availability within GNU-Radio environment. The result shows the sensing outputs data obtained by scanning wireless activities in the 2.4 GHz frequency band, necessary for the determination of the spectrum holes.},
	keywords = {Cognitive Radio (CR), Energy Detector(ED), Gnuradio, Raspberry Pi, Software defined Radio (SDR), Spectrum Sensing, USRP},
	url = {http://ipco-co.com/PET_Journal/vol20-ACECS/12.pdf},
	author = {Soumaya, El Barrak and Abdelouahid, Lyhyaoui and Antonio, Puliafito and Salvatore, Serrano}
}
