Projects / Programmes
Advanced modelling of radio channels using ray-optical and numerical meshless methods
| Code |
Science |
Field |
Subfield |
| 2.08.00 |
Engineering sciences and technologies |
Telecommunications |
|
| Code |
Science |
Field |
| 2.02 |
Engineering and Technology |
Electrical engineering, Electronic engineering, Information engineering |
radio wave propagation, radio signal prediction, numerical modelling, time-domain differential techniques, prediction software
Data for the last 5 years (citations for the last 10 years) on
April 18, 2024;
A3 for period
2018-2022
Data for ARIS tenders (
04.04.2019 – Programme tender,
archive
)
| Database |
Linked records |
Citations |
Pure citations |
Average pure citations |
| WoS |
305 |
2,701 |
2,165 |
7.1 |
| Scopus |
482 |
4,631 |
3,716 |
7.71 |
Researchers (13)
| no. |
Code |
Name and surname |
Research area |
Role |
Period |
No. of publicationsNo. of publications |
| 1. |
18174 |
PhD Boštjan Batagelj |
Telecommunications |
Researcher |
2021 - 2024 |
791 |
| 2. |
50192 |
Aljaž Blatnik |
Telecommunications |
Researcher |
2021 |
39 |
| 3. |
26454 |
PhD Matjaž Depolli |
Computer science and informatics |
Researcher |
2021 - 2024 |
99 |
| 4. |
26025 |
PhD Andrej Hrovat |
Telecommunications |
Researcher |
2021 - 2024 |
230 |
| 5. |
07109 |
PhD Tomaž Javornik |
Telecommunications |
Head |
2021 - 2024 |
435 |
| 6. |
28366 |
PhD Gregor Kosec |
Computer science and informatics |
Researcher |
2021 - 2024 |
161 |
| 7. |
50655 |
Peter Miklavčič |
Telecommunications |
Junior researcher |
2021 |
24 |
| 8. |
36309 |
PhD Tomi Mlinar |
Telecommunications |
Researcher |
2022 - 2024 |
165 |
| 9. |
15087 |
PhD Mihael Mohorčič |
Telecommunications |
Researcher |
2021 - 2024 |
476 |
| 10. |
56017 |
Grega Morano |
Telecommunications |
Researcher |
2023 - 2024 |
16 |
| 11. |
12765 |
PhD Roman Novak |
Telecommunications |
Researcher |
2021 - 2024 |
143 |
| 12. |
39080 |
PhD Filip Strniša |
Computer science and informatics |
Researcher |
2022 - 2024 |
24 |
| 13. |
17167 |
PhD Aleš Švigelj |
Telecommunications |
Researcher |
2021 - 2024 |
247 |
Organisations (2)
Abstract
Comprehensive understanding of radio wave propagation is essential to any further development of wireless networks. Ultra-dense, ultra-reliable and low latency communications, massive antenna systems, highly dynamic mobility, location aware communications, widespread use of artificial intelligence, shift toward higher frequency bands— all these aspects and concepts included in 6G wireless networks vision, require better knowledge of radio wave propagation. Widely deployed wireless networks up to 4G looked at provision of the communication links, at first between humans, then between humans and content and service providers, while the 5G extends communication beyond the human users and introduces machine-to-machine communications. The diversity of communications brings new demands in the system requirements. In addition to the high data rates, high expectations for communication link latency, reliability and density of the wireless devices are necessary. The 5G wireless systems address these challenges at physical layer by taking advantage of the spatial dimension of wireless link using smart antennas, beam forming and cooperative communications as well as allocation of new frequency bands at UHF and mm-wave frequencies. While the 5G wireless networks are in their deployment phase, the research in the next generation has already started. One of the main 6G research objectives is the increase of the intelligence in all network aspects in order to manage the ever-increasing heterogeneity in communicating devices and their key performance indicators. Such intelligence requires detailed knowledge of the signal propagation properties at new frequency bands and in complex environments. In telecommunications the signal wavelength is small compared to the physical features of objects, therefore ray-tracing techniques provide solutions that are efficient, fast and still within time constraints. However, the deterministic ray-tracing techniques model only a subset of the propagation mechanisms and in their present form do not guarantee appropriate modelling for the continued increase of wireless systems data rates, throughput and reliability. On the other hand, accurate numerical approach of solving fundamental Maxwell's equations is best suited for modelling electrical field interactions with physical objects where characteristic dimensions of a computing domain is typically on the order of a few wavelengths in size. However, the increased computing capabilities and the demand for better characterization of communication channels that cover smaller and extremely irregular areas make numerical methods, especially those for electrically larger problems, a competing approach to the advanced ray-tracing techniques. In the proposed project, we are studying methods and approaches for radio wave propagation at carrier frequencies foreseen for future communication systems and supporting the future network intelligence. Adaptation of the numerical methods using meshless concepts for their greater acceptability in electrically large problems is a viable competition to accuracy improvements of the existing deterministic models, with the ray-tracing techniques being among most popular. We propose a comprehensive evaluation and adaptation of the two competing approaches for the telecommunication channel modelling. The objective of the research is to study ways of overcoming excessive time requirements while providing acceptable channel modelling accuracy in demanding irregular environments. Our focus will be on environments with no simple geometrical description, such as detail-rich small radio cells. Finally, we will assess the trade-offs between both techniques in terms of speed and accuracy.
