TY - GEN
T1 - Spectrum sensing for a subdivided band in cognitive radio networks
AU - Paul, Prosanta
AU - Xin, Chunsheng
AU - Song, Min
AU - Zhao, Yanxiao
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015/10/2
Y1 - 2015/10/2
N2 - Spectrum sensing plays a critical role in cognitive radio networks. Most of existing works on spectrum sensing adopted energy detection which takes samples on a band and then compares the summation with a threshold to determine the state of the band. However, if a licensed band is subdivided by the primary users, such as in the unlicensed WiFi band, the energy detection faces a challenge. The threshold used to decide if there is a PU signal on the band now depends on the number of sub-bands that are being used by primary users, since the received signal power on the band is now dependent on the number of used sub-bands. In this work, we propose a wavelet based spectrum sensing approach that does not depend on the number of used sub-bands and adaptively detects PU signals on a licensed band. We use the measured real world signals to test the approach. The simulation results indicate that the proposed approach can effectively detect the PU signal on a licensed band without needing the knowledge of band subdivision. In addition, the comparative study with the existing techniques is performed to evaluate two performance metrics, true detection and false alarm, for primary users signal detection.
AB - Spectrum sensing plays a critical role in cognitive radio networks. Most of existing works on spectrum sensing adopted energy detection which takes samples on a band and then compares the summation with a threshold to determine the state of the band. However, if a licensed band is subdivided by the primary users, such as in the unlicensed WiFi band, the energy detection faces a challenge. The threshold used to decide if there is a PU signal on the band now depends on the number of sub-bands that are being used by primary users, since the received signal power on the band is now dependent on the number of used sub-bands. In this work, we propose a wavelet based spectrum sensing approach that does not depend on the number of used sub-bands and adaptively detects PU signals on a licensed band. We use the measured real world signals to test the approach. The simulation results indicate that the proposed approach can effectively detect the PU signal on a licensed band without needing the knowledge of band subdivision. In addition, the comparative study with the existing techniques is performed to evaluate two performance metrics, true detection and false alarm, for primary users signal detection.
KW - Edge detection
KW - Multi-scale summation
KW - Spectrum sensing
KW - Wavelet transform
UR - http://www.scopus.com/inward/record.url?scp=84959431433&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84959431433&partnerID=8YFLogxK
U2 - 10.1109/ICCCN.2015.7288471
DO - 10.1109/ICCCN.2015.7288471
M3 - Conference contribution
AN - SCOPUS:84959431433
T3 - Proceedings - International Conference on Computer Communications and Networks, ICCCN
BT - 24th International Conference on Computer Communications and Networks, ICCCN 2015
T2 - 24th International Conference on Computer Communications and Networks, ICCCN 2015
Y2 - 3 August 2015 through 6 August 2015
ER -