@article {646,
	title = {Random sampling for effective spectrum sensing in cognitive radio time slotted environment},
	journal = {Physical Communication},
	volume = {49},
	year = {2021},
	month = {10/2021},
	type = {Research},
	abstract = {<p>In the context of wireless communication, Cognitive Radio has been proposed to ensure an optimal use of the spectrum. It divides the communication transceivers into two categories. Primary User has the priority to use the spectrum band while secondary user is an opportunistic user that can transmit on that band whenever it is available. In order to determine whether a concerned band is occupied or vacant, spectrum sensing functionality is needed together with an appropriate algorithm able to analyze the produced data in order to understand whether a primary user is transmitting or not. In this paper, we contribute by investigating a narrowband spectrum sensing based on two proposed parameters obtained randomly sampling the signal and a Multilayer Perceptron neural network (MLP) classifier. We show that the use of random sampling is more effective than the use of classical uniform sampling. We analyzed the activity status in the GSM channel by using a synthetically generated signal: the signal has been sampled using both uniform and random sampling, than it has been reconstructed and finally classified with the aim of a neural network based classifier. The performances in terms of Receiver Operating Characteristic curves for different Signal to Noise Ratio are presented.</p>
},
	keywords = {Classification, Cognitive Radio, GSM, Neural network, Random sampling, Spectrum Sensing},
	issn = {1874-4907},
	doi = {https://doi.org/10.1016/j.phycom.2021.101482},
	url = {https://www.sciencedirect.com/science/article/pii/S1874490721002196},
	author = {S. Serrano and M. Scarpa and A. Maali and N. Boumazz},
	editor = {A. Soulmani}
}
@conference { 11570_3115060,
	title = {Application of MVDR and MUSIC spectrum sensing techniques with implementation of Node{\textquoteright}s prototype for cognitive radio Ad Hoc networks},
	booktitle = {ACM International Conference Proceeding Series},
	volume = {130526},
	year = {2017},
	publisher = {Association for Computing Machinery},
	organization = {Association for Computing Machinery},
	address = {New York, NY 10121-0701},
	keywords = {1707, AdHoc Networks, Cognitive Radio, Computer Networks and Communications, GNU-Radio, Human-Computer Interaction, IoT, MUSIC, MVDR, Software, Spectrum Sensing, USRPb200},
	isbn = {9781450352819} pages = {101{\textendash}106},
	doi = {10.1145/3128128.3128144},
	url = {http://portal.acm.org/},
	author = {El Barrak, Soumaya and Lyhyaoui, Abdelouahid and El Gonnouni, Amina and Puliafito, Antonio and Serrano, Salvatore}
}
@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}
}
