An Extensible Toolkit For Real-Time High-Performance Wideband Spectrum Sensing

This document describes the design process of a software toolkit to perform high-performance wideband spectrum sensing. A prominent application of this is Cognitive Radio, a technique that aims to make more efficient use of the available radio spectrum. An extensive theoretical analysis will be performed. Various non-uniform sampling techniques will be discussed, such as coprime and circular sparse sampling. An algorithm to reconstruct the PSD of sub-Nyquist sampled signals will be developed and a detection algorithm which uses this PSD will be proposed. This analysis will be utilised to implement an extensible software toolkit written in Python. The software architecture and various design patterns that were utilised to structure the toolkit will be described and its quality and performance will be analysed. The hardware used for data acquisition, a USRP N210, will be introduced. The work will be concluded with a conclusion and its discussion.Electrical EngineeringCircuits and SystemsElectrical Engineering, Mathematics and Computer Scienc