  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.
