  Pathloss is typically modeled using a log-distance power law with a
large-scale fading term that is log-normal. However, the received signal is
affected by the dynamic range and noise floor of the measurement system used to
sound the channel, which can cause measurement samples to be truncated or
censored. If the information about the censored samples are not included in the
estimation method, as in ordinary least squares estimation, it can result in
biased estimation of both the pathloss exponent and the large scale fading.
This can be solved by applying a Tobit maximum-likelihood estimator, which
provides consistent estimates for the pathloss parameters. This letter provides
information about the Tobit maximum-likelihood estimator and its asymptotic
variance under certain conditions.
