IEICE TRANSACTIONS on Communications
Radio Propagation Prediction Method Using Point Cloud Data Based on Hybrid of Ray-Tracing and Effective Roughness Model in Urban Environments
Summary :
This paper proposes a radio propagation prediction method that uses point cloud data based on a hybrid of the ray-tracing (RT) method and an effective roughness (ER) model in urban environments for the fifth generation mobile communications system using high frequency bands. The proposed prediction method incorporates propagation characteristics that consider diffuse scattering from surface irregularities. The validity of the proposed method is confirmed by comparisons of measurement and prediction results gained from the proposed method and a conventional RT method based on power delay and angular profiles. From predictions based on the power delay and angular profiles, we find that the proposed method, assuming the roughness of σh=1mm, accurately predicts the propagation characteristics in the 20GHz band for urban line-of-sight environments. The prediction error for the delay spread is 2.1ns to 9.7ns in an urban environment.
- Publication
- IEICE TRANSACTIONS on Communications Vol.E102-B No.1 pp.51-62
- Publication Date
- 2019/01/01
- Publicized
- 2018/07/10
- Online ISSN
- 1745-1345
- DOI
- 10.1587/transcom.2017EBP3436
- Type of Manuscript
- PAPER
- Category
- Antennas and Propagation
Authors
Minoru INOMATA
NTT DOCOMO, INC.
Tetsuro IMAI
NTT DOCOMO, INC.
Koshiro KITAO
NTT DOCOMO, INC.
Yukihiko OKUMURA
NTT DOCOMO, INC.
Motoharu SASAKI
NTT Access Network Service Systems Laboratories
Yasushi TAKATORI
NTT Access Network Service Systems Laboratories
Keyword
Latest Issue
Copyrights notice of machine-translated contents
The copyright of the original papers published on this site belongs to IEICE. Unauthorized use of the original or translated papers is prohibited. See IEICE Provisions on Copyright for details.
Cite this
Copy
Minoru INOMATA, Tetsuro IMAI, Koshiro KITAO, Yukihiko OKUMURA, Motoharu SASAKI, Yasushi TAKATORI, "Radio Propagation Prediction Method Using Point Cloud Data Based on Hybrid of Ray-Tracing and Effective Roughness Model in Urban Environments" in IEICE TRANSACTIONS on Communications,
vol. E102-B, no. 1, pp. 51-62, January 2019, doi: 10.1587/transcom.2017EBP3436.
Abstract: This paper proposes a radio propagation prediction method that uses point cloud data based on a hybrid of the ray-tracing (RT) method and an effective roughness (ER) model in urban environments for the fifth generation mobile communications system using high frequency bands. The proposed prediction method incorporates propagation characteristics that consider diffuse scattering from surface irregularities. The validity of the proposed method is confirmed by comparisons of measurement and prediction results gained from the proposed method and a conventional RT method based on power delay and angular profiles. From predictions based on the power delay and angular profiles, we find that the proposed method, assuming the roughness of σh=1mm, accurately predicts the propagation characteristics in the 20GHz band for urban line-of-sight environments. The prediction error for the delay spread is 2.1ns to 9.7ns in an urban environment.
URL: https://global.ieice.org/en_transactions/communications/10.1587/transcom.2017EBP3436/_p
Copy
@ARTICLE{e102-b_1_51,
author={Minoru INOMATA, Tetsuro IMAI, Koshiro KITAO, Yukihiko OKUMURA, Motoharu SASAKI, Yasushi TAKATORI, },
journal={IEICE TRANSACTIONS on Communications},
title={Radio Propagation Prediction Method Using Point Cloud Data Based on Hybrid of Ray-Tracing and Effective Roughness Model in Urban Environments},
year={2019},
volume={E102-B},
number={1},
pages={51-62},
abstract={This paper proposes a radio propagation prediction method that uses point cloud data based on a hybrid of the ray-tracing (RT) method and an effective roughness (ER) model in urban environments for the fifth generation mobile communications system using high frequency bands. The proposed prediction method incorporates propagation characteristics that consider diffuse scattering from surface irregularities. The validity of the proposed method is confirmed by comparisons of measurement and prediction results gained from the proposed method and a conventional RT method based on power delay and angular profiles. From predictions based on the power delay and angular profiles, we find that the proposed method, assuming the roughness of σh=1mm, accurately predicts the propagation characteristics in the 20GHz band for urban line-of-sight environments. The prediction error for the delay spread is 2.1ns to 9.7ns in an urban environment.},
keywords={},
doi={10.1587/transcom.2017EBP3436},
ISSN={1745-1345},
month={January},}
Copy
TY - JOUR
TI - Radio Propagation Prediction Method Using Point Cloud Data Based on Hybrid of Ray-Tracing and Effective Roughness Model in Urban Environments
T2 - IEICE TRANSACTIONS on Communications
SP - 51
EP - 62
AU - Minoru INOMATA
AU - Tetsuro IMAI
AU - Koshiro KITAO
AU - Yukihiko OKUMURA
AU - Motoharu SASAKI
AU - Yasushi TAKATORI
PY - 2019
DO - 10.1587/transcom.2017EBP3436
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E102-B
IS - 1
JA - IEICE TRANSACTIONS on Communications
Y1 - January 2019
AB - This paper proposes a radio propagation prediction method that uses point cloud data based on a hybrid of the ray-tracing (RT) method and an effective roughness (ER) model in urban environments for the fifth generation mobile communications system using high frequency bands. The proposed prediction method incorporates propagation characteristics that consider diffuse scattering from surface irregularities. The validity of the proposed method is confirmed by comparisons of measurement and prediction results gained from the proposed method and a conventional RT method based on power delay and angular profiles. From predictions based on the power delay and angular profiles, we find that the proposed method, assuming the roughness of σh=1mm, accurately predicts the propagation characteristics in the 20GHz band for urban line-of-sight environments. The prediction error for the delay spread is 2.1ns to 9.7ns in an urban environment.
ER -
English
