A variable threshold for an energy detector using GNU radio

Spectrum is a natural resource and should be treated as such. Spectrum has dual use applications that range from short distance communication links such as Bluetooth to health, power systems, transport, smart city applications and space communications and exploration. Next Generation Networks (NGNs) are designed to connect millions of devices seamlessly and with high throughput rates in the aforementioned sectors and others not mentioned. The use of spectrum has to be efficiently utilized and appropriated. Cognitive radio communications serve to improve use of dwindling spectrum availability. Spectrum sensing is the first and critical technology in cognitive radio meant to determine radio parameters. Energy Detection (ED) is a spectrum sensing technology that has a low computational and operational complexity, a relatively fast spectrum sensing technique to other spectrum sensing technologies, and requires no knowledge of the primary user’s transmit signal properties such as modulation or error correction schemes. In its classical case, ED compares the signal energy received with a fixed detection threshold, estimated with an expected noise level. Noise however in practice varies randomly due to thermal variations, non-uniform movement of electrons, imperfections of semiconductor materials and external noise sources to mention a few. This creates a noise uncertainty phenomenon which negatively affects the fixed threshold approach used in classical ED. Development of an out-of-tree module for a variable threshold energy detector using the estimated noise power at each sample point is presented in this dissertation. GNU Radio software and Ettus Universal Software Radio Peripheral (USRP) hardware were used to simulate the performance of the proposed variable threshold energy detector. The Neyman-Pearson theory was adopted in achieving the proposed variable threshold energy detector. The variable threshold energy detector successfully sensed the presence of a primary user signal at 1.25% less the spectrum sensing time of the constant threshold. An ROC curve plot also showed that the proposed variable threshold energy detector had a better performance in general as opposed to the constant threshold energy detector at low signal-to-noise ratio levels