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A Phase Difference Based Cooperative Spectrum Sensing Scheme for Cognitive Radio Network

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Abstract

The increasing scarcity of spectrum resources is one of the most challenging issues to cognitive radio systems in 5G era. Traditional schemes fail to gain the balance between accuracy and complexity, which are the two of the most significant parameters to evaluate the performance of the spectrum sensing. In this paper, in order to improve the sensing accuracy and reduce the computation complexity, we propose a novel cooperative spectrum sensing scheme based on phase difference is proposed. By using the mean of Phase Difference (PD) as the test statistics, the proposed PD mean detection is formulated for efficient spectrum sensing and its performance is analyzed under Rayleigh fading channel and Gaussian noise, which has a low complexity of O(K) and is immune to the noise uncertainty in contrast to the energy detection scheme. Moreover, to improve performance of the sensing scheme based on phase difference by a single CR, we consider the cooperative scenario with multiple CR nodes. Simulation verifies that our scheme obtains 3–4 dB gains comparing with energy detection.

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Acknowledgment

This work was supported by the National Natural Science Foundation of China (61227801), the National Key Technology R&D Program of China (2015ZX03002008-002).

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Correspondence to Zheng Xie .

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© 2018 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Xie, Z., Huang, S., Zhang, Y., Feng, Z. (2018). A Phase Difference Based Cooperative Spectrum Sensing Scheme for Cognitive Radio Network. In: Long, K., Leung, V., Zhang, H., Feng, Z., Li, Y., Zhang, Z. (eds) 5G for Future Wireless Networks. 5GWN 2017. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 211. Springer, Cham. https://doi.org/10.1007/978-3-319-72823-0_49

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  • DOI: https://doi.org/10.1007/978-3-319-72823-0_49

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-72822-3

  • Online ISBN: 978-3-319-72823-0

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