Time-of-arrival estimation in OFDM-based cognitive radio systems

Abstract

Cognitive radio (CR) systems can efficiently utilize the radio spectrum due to their ability to sense environmental conditions and adapt their communications parameters (such as power, carrier frequency, and modulation) so as to enable dynamic reuse of the available spectrum. In this thesis, theoretical limits on time-of-arrival (TOA) estimation are derived for CR systems in the presence of interference. Specifically, closed form expressions are obtained for Cramer-Rao bounds (CRBs) on TOA estimation in orthogonal frequency division multiplexing (OFDM) based CR systems in various scenarios. Based on the CRB expressions, an optimal power allocation strategy that provides the best possible TOA estimation accuracy is proposed. This strategy considers the constraints imposed by regulatory emission mask and the sensed interference spectrum. The maximum likelihood (ML) TOA estimator is derived for an OFDM-based signalling scheme, and its performance is investigated against the theoretical limits offered by the CRB expressions. In addition, numerical results for the CRBs and ML TOA estimator are obtained and the effects of the optimal power allocation strategy on the accuracy of ML TOA estimator are examined in the absence/presence of interference. The use of optimal power allocation strategy instead of the conventional power assignment scheme is demonstrated to provide significant gains in terms of the TOA estimation accuracy. Analysis of the performance sensitivity of the optimal power allocation strategy to the uncertainty in spectrum estimation is performed, and the performance of optimal power allocation is observed to be consistently superior to that of the uniform power allocation even for substantially high values of spectral estimation errors.