@InProceedings{8081703,
  author = {S. Büyükçorak and G. K. Kurt and A. Yongaçoğlu},
  booktitle = {2017 25th European Signal Processing Conference (EUSIPCO)},
  title = {An empirical study on gamma shadow fading based localization},
  year = {2017},
  pages = {2709-2713},
  abstract = {In this paper, we propose a maximum likelihood estimator for received signal strength (RSS) based indoor localization systems by exploiting gamma shadow fading model. In order to investigate the validity of proposed method in a realistic environment, we develop a testbed based on Wi-Fi technology. Through experimental analyses, we first demonstrate the gamma distribution is a good fit to lognormal distribution, and both of them can sufficiently accurately characterize the empirical RSS observations. Then, we observe that gamma distribution is worth investigating for indoor localization compared to lognormal model because it provides superior accuracy. We further analyze the impacts of uncertainties of considered distributions' parameters on the localization performance via simulations.},
  keywords = {fading channels;gamma distribution;indoor navigation;log normal distribution;maximum likelihood estimation;RSSI;wireless LAN;received signal strength;indoor localization systems;Wi-Fi technology;gamma distribution;lognormal distribution;lognormal model;maximum likelihood estimator;gamma shadow fading based localization;Fading channels;Wireless fidelity;Maximum likelihood estimation;Analytical models;Microscopy;Europe;Positioning;received power level;gamma shadow fading;maximum likelihood estimator;Wi-Fi},
  doi = {10.23919/EUSIPCO.2017.8081703},
  issn = {2076-1465},
  month = {Aug},
  url = {https://www.eurasip.org/proceedings/eusipco/eusipco2017/papers/1570346861.pdf},
}

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