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Statistical Modeling and Estimation of Censored Pathloss Data

Gustafson, Carl LU ; Abbas, Taimoor LU ; Bolin, David and Tufvesson, Fredrik LU (2015) In IEEE Wireless Communications Letters 4(5). p.569-572
Abstract
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 in formation about the Tobit maximum-likelihood estimator and... (More)
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 in formation about the Tobit maximum-likelihood estimator and its asymptotic variance under certain conditions. (Less)
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Pathloss, maximum-likelihood estimation, ordinary least squares, censored data, truncated data, vehicular communication.
in
IEEE Wireless Communications Letters
volume
4
issue
5
pages
569 - 572
publisher
IEEE--Institute of Electrical and Electronics Engineers Inc.
external identifiers
  • scopus:84960341644
ISSN
2162-2345
DOI
10.1109/LWC.2015.2463274
language
English
LU publication?
yes
id
7c63fa15-e131-4e07-903e-4084ab56b49e (old id 7761077)
alternative location
http://arxiv.org/abs/1504.03977
date added to LUP
2015-08-13 10:06:35
date last changed
2017-06-11 03:16:15
@article{7c63fa15-e131-4e07-903e-4084ab56b49e,
  abstract     = {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 in formation about the Tobit maximum-likelihood estimator and its asymptotic variance under certain conditions.},
  author       = {Gustafson, Carl and Abbas, Taimoor and Bolin, David and Tufvesson, Fredrik},
  issn         = {2162-2345},
  keyword      = {Pathloss,maximum-likelihood estimation,ordinary least squares,censored data,truncated data,vehicular communication.},
  language     = {eng},
  number       = {5},
  pages        = {569--572},
  publisher    = {IEEE--Institute of Electrical and Electronics Engineers Inc.},
  series       = {IEEE Wireless Communications Letters},
  title        = {Statistical Modeling and Estimation of Censored Pathloss Data},
  url          = {http://dx.doi.org/10.1109/LWC.2015.2463274},
  volume       = {4},
  year         = {2015},
}