Energy detection for spectrum sensing in OFDM-based cooperative and non-cooperative radio networks - Salman, Emad Hmood (2018)
The Cognitive Radio (CR) concept aims to opportunistically access the different bandwidths of wireless spectrum with preventing harmful interference to the licensed users to address the fixed bands access issue. The Spectrum Sensing (SS) stage is crucial in CR system to reliably estimate the presenting of licensed user. This stage can be performed thorough several techniques to reuse the OFDM signal in 4G and 5G systems. The Energy Detection (ED) technique is the simplest and low computational complexity. However, it has some challenges in low Signal-to-Noise Ratio (SNR). In this thesis, we address the challenges in addition to reduce the computational complexity and improve the detection accuracy. Firstly, a new approximated closed-form expression is derived for the non-cooperative SS (NSS) based on ED technique to sense an OFDM signal. With the purpose of low SNR effect reduction, the expression is presented a novel Constant Local False Alarm Rate (CLFAR) with Constant Local Detection Rate (CLDR) algorithm, in which Secondary User (SU) can detect the licensed band in high noise variance medium accurately. Next, we developed a Constant Global False Alarm Rate (CGFAR) with Constant Global Detection Rate (CGDR) algorithm to mitigate the Cooperative SS (CSS) requirements. This algorithm can also work for big number of SUs that detect the OFDM signal. The last but not least, a new scheme of Modified Compressive SS (COMPSS) technique, proposed to significantly decrease the consumed power in Analog-to-Digital Convertors (ADCs). These stages are the Wavelet Transform based on pyramid algorithm, and the previous algorithms to apply this system on NSS and CSS networks. This cascaded COMPSS system does not require any signal reconstruction although it reduces the sub-Nyquist rate. Simulation results show that the analysis on the first algorithm has precise sensing and enhances the detection performance in low SNR case till -50 dB. In addition, it decreases the computational complexity. Moreover, the second algorithm improves the global decision through realizing the desired detection performance with low computational complexity. Besides, the number of SUs can be increased to 100 users. The cascaded system can compress and sense the licensed wideband with compression ratio till to 81.5% for one and multi SUs. The analytical results are validated the simulation results.