Deep-learning-based radio map reconstruction for V2X communications
Radio environment map (REM) reconstruction based on large-scale channel measurements
is a promising technology for future mobility services involving vehicle-to-everything (V2X) …
is a promising technology for future mobility services involving vehicle-to-everything (V2X) …
Image-driven spatial interpolation with deep learning for radio map construction
Radio maps are a promising technology that can boost the capability of wireless networks by
enhancing spectrum efficiency. Since spatial interpolation is a critical challenge to construct …
enhancing spectrum efficiency. Since spatial interpolation is a critical challenge to construct …
K-nearest neighbors gaussian process regression for urban radio map reconstruction
Y Zhang, S Wang - IEEE Communications Letters, 2022 - ieeexplore.ieee.org
Radio map is of great importance to interference control, network planning and resource
allocation in wireless communications. In this letter, we develop an accurate radio map …
allocation in wireless communications. In this letter, we develop an accurate radio map …
Radio map interpolation using graph signal processing
AEC Redondi - IEEE Communications Letters, 2017 - ieeexplore.ieee.org
Interpolating a radio map is a problem of great relevance in many scenarios such as network
planning, network optimization, and localization. In this letter, such a problem is tackled by …
planning, network optimization, and localization. In this letter, such a problem is tackled by …
Distributed radio map reconstruction for 5G automotive
VP Chowdappa, C Botella… - IEEE Intelligent …, 2018 - ieeexplore.ieee.org
Radio maps are expected to be an essential tool for the resource optimization and
management of 5G automotive. In this paper, we consider the problem of radio map …
management of 5G automotive. In this paper, we consider the problem of radio map …
3D radio map reconstruction based on generative adversarial networks under constrained aircraft trajectories
Three-dimensional (3D) radio map, which characterizes the spatial distribution of the
received signal strength (RSS) across a 3D space, can be a significant tool for wireless …
received signal strength (RSS) across a 3D space, can be a significant tool for wireless …
Deep completion autoencoders for radio map estimation
Y Teganya, D Romero - IEEE Transactions on Wireless …, 2021 - ieeexplore.ieee.org
Radio maps provide metrics such as power spectral density for every location in a
geographic area and find numerous applications such as UAV communications, interference …
geographic area and find numerous applications such as UAV communications, interference …
SICNN: Spatial interpolation with convolutional neural networks for radio environment mapping
R Hashimoto, K Suto - 2020 International Conference on …, 2020 - ieeexplore.ieee.org
This paper addresses the spatial interpolation problem in measurement-based radio
environment estimation. For accurate interpolation, we need to extract global and local radio …
environment estimation. For accurate interpolation, we need to extract global and local radio …
Quantized radio map estimation using tensor and deep generative models
Spectrum cartography (SC), also known as radio map estimation (RME), aims at crafting
multi-domain (eg, frequency and space) radio power propagation maps from limited sensor …
multi-domain (eg, frequency and space) radio power propagation maps from limited sensor …
RadioUNet: Fast radio map estimation with convolutional neural networks
In this paper we propose a highly efficient and very accurate deep learning method for
estimating the propagation pathloss from a point (transmitter location) to any point on a …
estimating the propagation pathloss from a point (transmitter location) to any point on a …