Blind Estimation of Primary User Traffic Parameters Under Sensing Errors

TL;DR

This paper derives bounds and estimators for primary user traffic parameters in cognitive radio, accounting for spectrum sensing errors, and analyzes their impact on estimation accuracy through theoretical and simulation results.

Contribution

It introduces closed-form bounds and maximum-likelihood estimators for traffic parameters considering sensing errors, a novel analysis in this context.

Findings

Derived Cramer-Rao bounds for traffic parameter estimation.

Presented maximum-likelihood estimators incorporating sensing errors.

Quantified the impact of sensing errors on estimation accuracy.

Abstract

In this work we investigate the bounds on the estimation accuracy of Primary User (PU) traffic parameters with exponentially distributed busy and idle times. We derive closed-form expressions for the Cramer-Rao bounds on the mean squared estimation error for the blind joint estimation of the PU traffic parameters, specifically, the duty cycle, and the mean arrival and departure rates. Moreover, we present the corresponding maximum-likelihood estimators for the traffic parameters. In addition, we derive a modified likelihood function for the joint estimation of traffic parameters when spectrum sensing errors are considered, and we present the impact of spectrum sensing errors on the estimation error via simulations. Finally, we consider a duty cycle estimator, common in traffic estimation literature, that is based on averaging the traffic samples. We derive, in closed-form, the mean squared estimation error of the considered estimator under spectrum sensing errors.