Analysis of α-domain noise and feature detection for cognitive radio systems

Authors:
Xiaoying Gan;Miao Xu;Zhongren Cao;Feng Yang;Yuan Zhou;Wei Zhang
Affiliations:
Shanghai Jiao Tong University, Shanghai, China;Shanghai Jiao Tong University, Shanghai, China;University of California San Diego, La Jolla, CA;Shanghai Jiao Tong University, Shanghai, China;Huawei Technologies Co., Ltd., Bantian Longgang, Shenzhen, P.R. China;Huawei Technologies Co., Ltd., Bantian Longgang, Shenzhen, P.R. China
Venue:
Proceedings of the 6th International Wireless Communications and Mobile Computing Conference
Year:
2010

Citing 2
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NeXt generation/dynamic spectrum access/cognitive radio wireless networks: a survey

Computer Networks: The International Journal of Computer and Telecommunications Networking
Collaborative cyclostationary spectrum sensing for cognitive radio systems

IEEE Transactions on Signal Processing

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Abstract

Cyclostationary feature detection is capable of improving sensing performance in Cognitive Radio systems. The maximum over spectral on cyclostationary domain is called α-domain. α-domain feature detection will greatly reduce computational complexity with respect to prior-knowledge of carrier frequency. To select the threshold for α-domain feature detection under a given noise level and miss detection probability Pf, we need the expression of α-domain noise distribution. In this paper, Generalized Extreme Value (GEV) distribution is introduced and found as the noise distribution on α-domain. Maximum likelihood estimation is applied to estimate the parameters of GEV distribution. Based on GEV distribution, close form of detection threshold λth in terms of false alarm probability Pf is obtained. The validation of α-domain noise distribution is confirmed by the Monte-Carlo simulation.