Research on Base Station Location Select Method for Multi-type Terminal Scenarios in 5G Industrial Private Network
At present, 5G technology as an important technology to support the upgrade of industrial be wireless, and the organic integration of industrial applications will further stimulate the innovation vitality of the industrial community. However, with the development of mobile edge computing that relies on high throughput data transmission such as video streaming and the gradual emergence of smart industrial parks, the existing related work oriented to fixed terminals can no longer meet the needs of smart manufacturing scenarios, which poses a new challenge to the base station deployment method for industrial private networks characterized by the presence of dynamic terminals. This paper takes the industrial private network as the research object, proposes an improved throughput calculation model for dynamic terminals in industrial scenarios, through the channel parameters measured in the real industrial zone, combined with the known paths of dynamic terminals, to quantify the impact of non-uniform medium on signal quality in industrial scenes. On this basis, according to the characteristics of the scene where there are multiple types of dynamic and static mixed terminals, combined with the signal loss of the path of the mobile terminals, to establish a throughput calculation model oriented to the industrial scene; Finally, with the objective of optimal signal quality at terminals, we establish an optimization model for the deployment of base station locations in industrial private networks applicable to large-scale machine communication scenarios and solve the optimal site selection results.
Authors
- Kui Zhang
- Luo Zhao
- Junfeng Zhu (ORCID: https://orcid.org/0000-0002-3120-5290)
- Runze Zhao (ORCID: https://orcid.org/0000-0002-4146-4114)
- Haowen Yin
Institutions
- China Electronics Technology Group Corporation (CN)
Publication Details
- Published
- 2024-09-23
- DOI
- https://doi.org/10.1109/icedcs64328.2024.00154
- Citations
- 1
- Primary Topic
- E-commerce and Technology Innovations
- Type
- article
- Field-Weighted Citation Impact
- 0.68
Funders
- National Natural Science Foundation of China