Research Article
Adaptive Threshold Technique for Spectrum Sensing Cognitive Radios Under Gaussian Channel Estimation Errors
@INPROCEEDINGS{10.1007/978-3-319-95450-9_15, author={Syed Naqvi and Aamir Shaikh and Krishan Khatri and Altaf Mugheri and Shabbir Ahmed}, title={Adaptive Threshold Technique for Spectrum Sensing Cognitive Radios Under Gaussian Channel Estimation Errors}, proceedings={Emerging Technologies in Computing. First International Conference, iCETiC 2018, London, UK, August 23--24, 2018, Proceedings}, proceedings_a={ICETIC}, year={2018}, month={7}, keywords={Adaptive spectrum sensing Collaborative spectrum sensing Gaussian channel estimation errors}, doi={10.1007/978-3-319-95450-9_15} }- Syed Naqvi
Aamir Shaikh
Krishan Khatri
Altaf Mugheri
Shabbir Ahmed
Year: 2018
Adaptive Threshold Technique for Spectrum Sensing Cognitive Radios Under Gaussian Channel Estimation Errors
ICETIC
Springer
DOI: 10.1007/978-3-319-95450-9_15
Abstract
Spectrum sensing helps cognitive wireless users to gather RF information regarding presence or absence of spectral holes. These spectral holes are not permanent in nature. These are exploited by cognitive users in secondary fashion in such a way that they do not create harmful interference for primary users (PU). Thus, on sudden arrival of a PU, secondary user must vacate those bands for PU because they are high priority users in comparison to cognitive users. The receiver circuit of cognitive radio estimates the received signal and noise parameters and computes a test statistic. This statistic is compared with a pre-set threshold. However, under realistic scenarios, wireless communication channels behave as time-varying entities. Hence, received signal as well as noise varies significantly. The variation in estimated receiver parameters results in deteriorated detection performance for fixed-threshold sensors. In this paper, it is assumed that there are Gaussian estimation errors in received signal. Under this case, an adaptive threshold based testing rule is applied to explore the performance of spectrum sensing radios under adaptive threshold rule. The results clearly recommend the use of proposed algorithm for received signal with Gaussian channel estimation errors. The results show that the proposed method significantly improves the detection performance of the considered cognitive radio i.e. for a false alarm rate of 0.1, the detection probability of the proposed system improves more than 3 times in comparison to the classic cognitive radio under Gaussian Channel estimation errors. The proposed technique can be utilized for future intelligent radios for 5G wireless networks.