| Cognitive radio is one of the most promising technologies to address the spectrum scarcity problem. Cognitive radio requires spectrum sensing, which is used by unlicensed users to opportunistically access the licensed spectrum. Spectrum sensing using energy detection offers low-cost and low-complexity. In this thesis, a comprehensive performance analysis of energy detection based spectrum sensing is developed. Detection performance over composite (fading and shadowing) channels is first investigated using the K and KG channel models. To further facilitate analysis of energy detection over different wireless channels, a unified channel model based on a mixture gamma distribution is developed. The unified model can accurately represent most existing channel models. A single-value performance metric, the area under the receiver operating characteristic curve, is proposed to measure the overall detection capability, and is investigated over various wireless fading channels. The energy detection based cooperative spectrum sensing is also studied, which can largely improve the detection performance. Since spectrum sensing is required to identify activities of licensed users at a very low signal-to-noise ratio (SNR), performance of energy detection with low SNR is also analyzed in this thesis. |
