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- W2154911016 abstract "Many spectrum sensing techniques have been proposed in the literature to enable cognitive radio technology. However, their reliability when primary users have very low signal-to-noise ratio (SNR) in the presence of noise uncertainty remains a challenging problem. This paper focuses on detecting wireless microphone signals in the presence of noise uncertainty. Power Spectrum Density (PSD)-based sensing has been proposed in the literature as the best sensing algorithm for wireless microphones. However, when there is noise uncertainty, PSD-based sensing performance is severely degraded. To solve this problem, eignevalues-based blind sensing, which does not need noise information, have been proposed. In this paper, we present a new adaptive spectrum sensing algorithm that outperforms both PSD-based sensing and the eigenvalues-based sensing in the presence of noise uncertainty. The algorithm combines the decisions of the two algorithms, and then, adapts the decision threshold required for the PSD-based sensing in an iterative way. Simulation results show that the proposed spectrum sensing algorithm outperforms the PSD-based sensing in the presence of 1 dB noise uncertainty by more than 2 dBs. At the same level of noise uncertainty, our algorithm outperforms the eigenvalue-based sensing by 1.2 dBs." @default.
- W2154911016 created "2016-06-24" @default.
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- W2154911016 date "2011-09-01" @default.
- W2154911016 modified "2023-09-28" @default.
- W2154911016 title "Adaptive spectrum sensing of wireless microphones with noise uncertainty" @default.
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- W2154911016 doi "https://doi.org/10.1109/pimrc.2011.6140000" @default.
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