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Experimental detection of mobile satellite transmissions with cyclostationary features
Author(s) -
Dimc Franc,
Baldini Gianmarco,
Kandeepan Sithamparanathan
Publication year - 2014
Publication title -
international journal of satellite communications and networking
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.388
H-Index - 39
eISSN - 1542-0981
pISSN - 1542-0973
DOI - 10.1002/sat.1081
Subject(s) - cyclostationary process , computer science , cognitive radio , telecommunications link , electronic engineering , real time computing , fast fourier transform , autocorrelation , communications satellite , fading , telecommunications , satellite , algorithm , wireless , engineering , channel (broadcasting) , statistics , decoding methods , mathematics , aerospace engineering
Summary One of the important functions of cognitive radio (CR) technology is spectrum sensing. The implementation of an efficient spectrum sensing function can be quite challenging because of various factors such as multi‐path fading, low signal‐to‐noise ratio of the radio communication services to be detected and the requirement to detect and analyze the signal in a short time. As a consequence, it is important to quantitatively assess the performance of spectrum sensing techniques in various scenarios. This paper investigates different digital signal processing techniques for spectrum sensing in the context of mobile satellite transmissions: power sensing, cyclostationary sensing, efficient cyclostationary sensing based on FFT accumulation method and strip spectral correlation algorithm. This paper presents experimental results on the cyclostationary properties of GSM Thuraya mobile satellite communications in various conditions both for the uplink and downlink channels. The receiver operating characteristics are computed, and the results are presented for different algorithms and different positions of the satellite terminals. The experimental results show that the cyclostationary‐feature‐based detection can be robust compared to energy‐based technique for low signal‐to‐noise ratio levels. Copyright © 2014 John Wiley & Sons, Ltd.