Deep learning-based signal strength prediction using geographical images and expert knowledge
Methods for accurate prediction of radio signal quality parameters are crucial for
optimization of mobile networks, and a necessity for future autonomous driving solutions …
optimization of mobile networks, and a necessity for future autonomous driving solutions …
City-wide signal strength maps: Prediction with random forests
Signal strength maps are of great importance to cellular providers for network planning and
operation, however they are expensive to obtain and possibly limited or inaccurate in some …
operation, however they are expensive to obtain and possibly limited or inaccurate in some …
A deep learning network planner: Propagation modeling using real-world measurements and a 3D city model
In urban scenarios, network planning requires awareness of the notoriously complex
propagation environment by accounting for blocking, diffraction, and reflection on buildings …
propagation environment by accounting for blocking, diffraction, and reflection on buildings …
Enhanced MDT-based performance estimation for AI driven optimization in future cellular networks
HN Qureshi, A Imran, A Abu-Dayya - IEEE Access, 2020 - ieeexplore.ieee.org
Minimization of drive test (MDT) allows coverage estimation at a base station by leveraging
measurement reports gathered at the user equipment (UE) without the need for drive tests …
measurement reports gathered at the user equipment (UE) without the need for drive tests …
Qoe evaluation in adaptive streaming: Enhanced mdt with deep learning
H Gokcesu, O Ercetin, G Kalem, S Ergut - Journal of Network and Systems …, 2023 - Springer
We propose an architecture for performing virtual drive tests for mobile network performance
evaluation by facilitating radio signal strength data from user equipment. Our architecture …
evaluation by facilitating radio signal strength data from user equipment. Our architecture …
Data-driven network simulation for performance analysis of anticipatory vehicular communication systems
B Sliwa, C Wietfeld - IEEE Access, 2019 - ieeexplore.ieee.org
The provision of reliable connectivity is envisioned as a key enabler for future autonomous
driving. Anticipatory communication techniques have been proposed for proactively …
driving. Anticipatory communication techniques have been proposed for proactively …
A unified prediction framework for signal maps: Not all measurements are created equal
Signal maps are essential for the planning and operation of cellular networks. However, the
measurements needed to create such maps are expensive, often biased, not always …
measurements needed to create such maps are expensive, often biased, not always …
DRaGon: Mining latent radio channel information from geographical data leveraging deep learning
Radio channel modeling is one of the most fundamental aspects in the process of designing,
optimizing, and simulating wireless communication networks. In this field, long-established …
optimizing, and simulating wireless communication networks. In this field, long-established …
TinyDRaGon: Lightweight radio channel estimation for 6G pervasive intelligence
Due to the emerging challenges with future 6G networks such as high data rates and the
need for remarkably low latency, future wireless communication systems must be planned …
need for remarkably low latency, future wireless communication systems must be planned …
Not in my neighborhood: A user equipment perspective of cellular planning under restrictive EMF limits
The installation of base station (BS) sites is regulated by a variety of laws at international,
national, and local levels. While international regulations are already severe, the national …
national, and local levels. While international regulations are already severe, the national …