TY - GEN
T1 - Soft decision Cooperative Spectrum Sensing based upon noise uncertainty estimation
AU - Farag, Hossam M.
AU - Mohamed, Ehab Mahmoud
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015/9/8
Y1 - 2015/9/8
N2 - Spectrum Sensing (SS) constitutes the most critical task in Cognitive Radio ( CR) systems for Primary User (PU) detection. Cooperative Spectrum Sensing (CSS) is introduced to enhance the detection reliability of the PU in fading environments. In this paper, we propose a soft decision based CSS algorithm using energy detection by taking into account the noise uncertainty effect. In the proposed algorithm, two threshold levels are utilized based on predicting the current PU activity, which can be successfully expected using a simple successive averaging process with time. The two threshold levels are evaluated based on estimating the noise uncertainty factor. In addition, they are toggled in a dynamic manner to compensate the noise uncertainty effect and to increase the probability of detection and decrease the probability of false alarm. Theoretical analysis is performed on the proposed algorithm to evaluate its enhanced false alarm and detection probabilities over the conventional soft decision CSS using different combining schemes. In addition, simulation results show the high efficiency of the proposed scheme compared to the conventional soft decision CSS, with high computational complexity enhancements.
AB - Spectrum Sensing (SS) constitutes the most critical task in Cognitive Radio ( CR) systems for Primary User (PU) detection. Cooperative Spectrum Sensing (CSS) is introduced to enhance the detection reliability of the PU in fading environments. In this paper, we propose a soft decision based CSS algorithm using energy detection by taking into account the noise uncertainty effect. In the proposed algorithm, two threshold levels are utilized based on predicting the current PU activity, which can be successfully expected using a simple successive averaging process with time. The two threshold levels are evaluated based on estimating the noise uncertainty factor. In addition, they are toggled in a dynamic manner to compensate the noise uncertainty effect and to increase the probability of detection and decrease the probability of false alarm. Theoretical analysis is performed on the proposed algorithm to evaluate its enhanced false alarm and detection probabilities over the conventional soft decision CSS using different combining schemes. In addition, simulation results show the high efficiency of the proposed scheme compared to the conventional soft decision CSS, with high computational complexity enhancements.
UR - https://www.scopus.com/pages/publications/84947732456
U2 - 10.1109/ICCW.2015.7247412
DO - 10.1109/ICCW.2015.7247412
M3 - Conference contribution
AN - SCOPUS:84947732456
T3 - 2015 IEEE International Conference on Communication Workshop, ICCW 2015
SP - 1623
EP - 1628
BT - 2015 IEEE International Conference on Communication Workshop, ICCW 2015
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - IEEE International Conference on Communication Workshop, ICCW 2015
Y2 - 8 June 2015 through 12 June 2015
ER -