Spectrum sensing algorithm based on autocorrelation energy in cognitive radio networks

Shengwei Ren; Li Zhang; Shibing Zhang

doi:10.1117/12.2262050

7 October 2016 Spectrum sensing algorithm based on autocorrelation energy in cognitive radio networks

Shengwei Ren, Li Zhang, Shibing Zhang

Proceedings Volume 9902, Fourth International Conference on Wireless and Optical Communications; 99020G (2016) https://doi.org/10.1117/12.2262050
Event: Fourth International Conference on Wireless and Optical Communications, 2016, Beijing, China

Abstract

Cognitive radio networks have wide applications in the smart home, personal communications and other wireless communication. Spectrum sensing is the main challenge in cognitive radios. This paper proposes a new spectrum sensing algorithm which is based on the autocorrelation energy of signal received. By taking the autocorrelation energy of the received signal as the statistics of spectrum sensing, the effect of the channel noise on the detection performance is reduced. Simulation results show that the algorithm is effective and performs well in low signal-to-noise ratio. Compared with the maximum generalized eigenvalue detection (MGED) algorithm, function of covariance matrix based detection (FMD) algorithm and autocorrelation-based detection (AD) algorithm, the proposed algorithm has 2 ~ 11 dB advantage.

Citation Download Citation

Shengwei Ren, Li Zhang, and Shibing Zhang "Spectrum sensing algorithm based on autocorrelation energy in cognitive radio networks", Proc. SPIE 9902, Fourth International Conference on Wireless and Optical Communications, 99020G (7 October 2016); https://doi.org/10.1117/12.2262050

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