TY - GEN
T1 - Low complexity trace based spectrum sensing algorithms
T2 - 17th IEEE International Conference on Communication Technology, ICCT 2017
AU - Yang, Xi
AU - Lei, Kejun
AU - Tan, Weiqiang
AU - Zhang, Yinhang
AU - Li, Shu
AU - Wu, Hao
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/7/2
Y1 - 2017/7/2
N2 - In this paper, the multi-antenna spectrum sensing for complex signals are considered. The totally-blind and half-blind spectrum sensing algorithms based on the trace of the sample covariance matrix (SCM) with low computing complexity are proposed. The former can carry out spectrum sensing without prior knowledge of the noise variance, wireless channel and primary signal, and the latter only requires prior knowledge of the noise variance. The analytical expressions for the probability of false alarm and the theoretical detection thresholds for them are also presented. A performance comparison between the proposed methods and other existing methods, such as the energy detector (ED), the covariance absolute value based method, the generalized likelihood ratio test (GLRT) based method and the eigenvalue based methods, is demonstrated. Simulation results show that the new methods can produce reliable sensing results, especially the totally-blind method exhibits higher detection probability than other existing detection techniques.
AB - In this paper, the multi-antenna spectrum sensing for complex signals are considered. The totally-blind and half-blind spectrum sensing algorithms based on the trace of the sample covariance matrix (SCM) with low computing complexity are proposed. The former can carry out spectrum sensing without prior knowledge of the noise variance, wireless channel and primary signal, and the latter only requires prior knowledge of the noise variance. The analytical expressions for the probability of false alarm and the theoretical detection thresholds for them are also presented. A performance comparison between the proposed methods and other existing methods, such as the energy detector (ED), the covariance absolute value based method, the generalized likelihood ratio test (GLRT) based method and the eigenvalue based methods, is demonstrated. Simulation results show that the new methods can produce reliable sensing results, especially the totally-blind method exhibits higher detection probability than other existing detection techniques.
KW - Cognitive radio
KW - Decision
KW - Multi-antenna spectrum sensing
KW - Sample covariance matrix (SCM)
KW - Trace
UR - https://www.scopus.com/pages/publications/85047727384
U2 - 10.1109/ICCT.2017.8359761
DO - 10.1109/ICCT.2017.8359761
M3 - 会议稿件
AN - SCOPUS:85047727384
T3 - International Conference on Communication Technology Proceedings, ICCT
SP - 882
EP - 887
BT - 2017 17th IEEE International Conference on Communication Technology, ICCT 2017
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 27 October 2017 through 30 October 2017
ER -