| Title |
5G Small Cell Transmission Point Density Planning |
| ID_Doc |
43911 |
| Authors |
Yazar, A; Deniz, N; Kaya, C; Çamas, RE; Ünal, R; Atilla, NE |
| Title |
5G Small Cell Transmission Point Density Planning |
| Year |
2023 |
| Published |
|
| DOI |
10.1109/SIU59756.2023.10224031 |
| Abstract |
One of the enabling technologies in the development process of 5th Generation (5G) cellular communications systems is small cell transmission points. Electricity poles are at the forefront of places where small cell transmission points, which are a technology complementary to millimeter wave communication, can be placed quickly. In this study, a novel machine learning-based approach has been developed to determine the density of 5G small cell transmission points that are placed on electricity poles in smart cities. In addition, exemplary field applications of this approach are provided. |
| Author Keywords |
5G; smart city; electricity distribution; small cells; machine learning |
| Index Keywords |
Index Keywords |
| Document Type |
Other |
| Open Access |
Open Access |
| Source |
Conference Proceedings Citation Index - Science (CPCI-S); Conference Proceedings Citation Index - Social Science & Humanities (CPCI-SSH) |
| EID |
WOS:001062571000237 |
| WoS Category |
Computer Science, Artificial Intelligence; Communication; Engineering, Electrical & Electronic; Telecommunications |
| Research Area |
Computer Science; Communication; Engineering; Telecommunications |
| PDF |
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