Proceedings of the 3rd International Conference on Mechatronics Engineering and Information Technology (ICMEIT 2019)

Design of Power Wireless Private Network Coverage Prediction System

Authors
Qianke Ai, Wenjiang Feng, Weinong Wu, Yuxiang Liu, Guojin Liu, Taotao Bao
Corresponding Author
Qianke Ai
Available Online April 2019.
DOI
https://doi.org/10.2991/icmeit-19.2019.56How to use a DOI?
Keywords
radio wave propagation model, coverage prediction, geographic information system.
Abstract
In this paper, according to the practical needs of the electric power wireless network coverage prediction, a propagation model based on real data and revised statistical prediction model (SPM) is proposed to predict the spatial field intensity distribution of the base station and improve the rationality and efficiency of the network planning and construction. The optimal parameters of SPM model parameters are obtained by least square method. On this basis, the coverage prediction with geographic information is proposed. The simulation results show that compared with SPM and LAP model, the proposed scheme can effectively analyze the signal loss intensity around the base station at any location in the map, so as to solve the signal planning problem of the base station.
Open Access
This is an open access article distributed under the CC BY-NC license.

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Proceedings
3rd International Conference on Mechatronics Engineering and Information Technology (ICMEIT 2019)
Part of series
Advances in Computer Science Research
Publication Date
April 2019
ISBN
978-94-6252-708-9
ISSN
2352-538X
DOI
https://doi.org/10.2991/icmeit-19.2019.56How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Qianke Ai
AU  - Wenjiang Feng
AU  - Weinong Wu
AU  - Yuxiang Liu
AU  - Guojin Liu
AU  - Taotao Bao
PY  - 2019/04
DA  - 2019/04
TI  - Design of Power Wireless Private Network Coverage Prediction System
BT  - 3rd International Conference on Mechatronics Engineering and Information Technology (ICMEIT 2019)
PB  - Atlantis Press
SN  - 2352-538X
UR  - https://doi.org/10.2991/icmeit-19.2019.56
DO  - https://doi.org/10.2991/icmeit-19.2019.56
ID  - Ai2019/04
ER  -