Source localization in a cognitive radio environment consisting of frequency and spatial mobility

Abstract

Cognitive radio presents a unique challenge to source localization in that the radio has the ability to adapt to the environment, thus rendering current localization techniques ineffective due to a shifting combination of spatial, frequency, and temporal parameters. For any localization scheme to be effective, it must be able to adapt over time as a cognitive radio adapts to its surroundings. In this thesis an extended semi range-based localization scheme is proposed to accomplish this task. The proposed scheme estimates the position of a cognitive radio using the collaborative spectrum sensing results of a wireless radio frequency sensor network in a cognitive radio environment. The central idea behind the proposed scheme is to exploit the relationships between spatial, frequency, and temporal parameters of the environment to solve for the position of the cognitive radio. The proposed scheme is modeled in the MATLAB programming language, and its efficacy is demonstrated through simulation. It is shown that over time the proposed scheme is capable of estimating the frequency band of operation and the location of a cognitive radio, and is thus capable of accounting for both frequency and spatial mobility inherent in the cognitive radio environment.