Statistical Modeling and Estimation of Censored Pathloss Data
Artikel i vetenskaplig tidskrift, 2015

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 is 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.

truncated data

maximum-likelihood estimation

ordinary least squares

censored data


vehicular communication


C. Gustafson

Lunds universitet

T. Abbas

Volvo Cars

David Bolin

Göteborgs universitet

Chalmers, Matematiska vetenskaper, Matematisk statistik

F. Tufvesson

Chalmers, Matematiska vetenskaper

IEEE Wireless Communications Letters

2162-2337 (ISSN)

Vol. 4 5 569-572 7174517


Elektroteknik och elektronik



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