@article{01GJHV0P29DH15RH12TF5P948K,
  abstract     = {{Indoor path loss models characterize the attenuation of signals between a transmitting and receiving antenna for a certain frequency and type of environment. Their use ranges from network coverage planning to joint communication and sensing applications such as localization and crowd counting. The need for this proposed geodesic path model comes forth from attempts at path loss-based localization on ships, for which the traditional models do not yield satisfactory path loss predictions. In this work, we present a novel pathfinding-based path loss model, requiring only a simple binary floor map and transmitter locations as input. The approximated propagation path is determined using geodesics, which are constrained shortest distances within path-connected spaces. However, finding geodesic paths from one distinct path-connected space to another is done through a systematic process of choosing space connector points and concatenating parts of the geodesic path. We developed an accompanying tool and present its algorithm which automatically extracts model parameters such as the number of wall crossings on the direct path as well as on the geodesic path, path distance, and direction changes on the corners along the propagation path. Moreover, we validate our model against path loss measurements conducted in two distinct indoor environments using DASH-7 sensor networks operating at 868 MHz. The results are then compared to traditional floor-map-based models. Mean absolute errors as low as 4.79 dB and a standard deviation of the model error of 3.63 dB is achieved in a ship environment, almost half the values of the next best traditional model. Improvements in an office environment are more modest with a mean absolute error of 6.16 dB and a standard deviation of 4.55 dB.}},
  articleno    = {{4903}},
  author       = {{Kaya, Abdil and De Beelde, Brecht and Joseph, Wout and Weyn, Maarten and Berkvens, Rafael}},
  issn         = {{1424-8220}},
  journal      = {{SENSORS}},
  keywords     = {{STATISTICAL-MODEL,MILLIMETER-WAVE,radio channel,path loss,signal strength,receivers,transmitters,wireless communication,computational modeling,path planning,electromagnetic propagation,loss measurement,propagation loss}},
  language     = {{eng}},
  number       = {{13}},
  pages        = {{17}},
  title        = {{Geodesic path model for indoor propagation loss prediction of narrowband channels}},
  url          = {{http://doi.org/10.3390/s22134903}},
  volume       = {{22}},
  year         = {{2022}},
}

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