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World Wide Web

, Volume 22, Issue 5, pp 2177–2207 | Cite as

Interference identification in smart grid communications

  • Jingping Yin
  • Weiwei Miao
  • Wen YeEmail author
  • Jiayan Teng
  • Chengling Jiang
  • Rui Liu
Article
  • 55 Downloads
Part of the following topical collections:
  1. Special Issue on Big Data Management and Intelligent Analytics

Abstract

The TD-LTE wireless private network for electric power systems is an important component of smart grids, and coverage analysis and interference identification are essential in operating and optimizing of power wireless private networks. This paper presents an approach to analyzing indoor and outdoor coverage scopes of cell radio signals and recognizing locations and sources of intra-network interference in the network deployed in a dense urban environment. This approach takes scenario modeling to represent terrain and on-ground objects given by digital maps, utilizes ray tracing to track the signal propagation trajectories, and calculates strength attenuation of radio signals due to signal propagation such as direct transmission, reflection, diffraction and refraction. The uniform grid is employed as the acceleration structure to speed up tracing signal propagation paths, and drive-testing measurement data and scenario-oriented propagation model calibration are used to improve analysis accuracy. Weak coverage spots and interference defect spots are defined and used to identify interference types and sources. We applied the approach to a tentative TD-LTE power wireless private network in a southern city in China, proving that the ray-tracing-based scheme is able to make precise analysis on coverage and interference in practical networks.

Keywords

Smart grid Wireless private network Coverage Interference Ray tracing Scenario 

Notes

Acknowledgements

The work in the paper comes from the science and technology project funded by State Grid Jiangsu Electric Power Company, and is also supported by National Natural Science Foundation of China (No.61320106006, No.61532006).

Supplementary material

11280_2018_589_MOESM1_ESM.pdf (1.2 mb)
(PDF 1.24 MB)

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Beijing University of Posts and TelecommunicationsBeijingChina
  2. 2.State Grid Jiangsu Electric Power CompanyNanjingChina
  3. 3.Nari Technology Development Limited CompanyNanjingChina

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