Energy Detection with Adaptive Threshold for Cognitive Radio
A. Nasrallah, Abdelkrim Hamza, Toufik Boukaba, Geneviève Baudoin, Azdine Messani · 2018
The problem of spectrum sensing has acquired new aspects with cognitive radio technology. The spectrum sensing is used to determine unused spectrum and to utilize those spectrums for unauthorized communication, without interfering. In the literature exist several strategies for satisfactory detection performance. Among the most basic sensing schemes, the Energy Detection (ED) offers, as advantages, simplicity, rapid analysis, and not needing prior information of the primary users PU's signal. However, a rapid degradation in the case of uncertain noise power value and the inability to distinguish between signals belonging to different systems, and between these signals and noise in low SNR are noticed as disadvantages. Within this context, this work proposes a new approach to improve energy detection algorithm based on adaptive threshold (EDAT). These adaptive thresholds are assessed based on the noise's uncertainty factor that can be estimated utilizing the energy obtained by re-sampling received signal through a sliding window. Analysis of the simulation results showed that ED with adaptive threshold displays a significant improvement in case of noise uncertainty, compared to ED.