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Identification of indoor radio environment properties based on channel state information using machine learning approaches

Author(s): Teodora Kocevska (Author), Andrej Hrovat (Supervisor), Aleksandra Rashkovska Koceva (Co-Supervisor)

Year: 2023

Type: Doctoral dissertation

Characterization of the indoor radio environment (RE) is a prerequisite for advances in the design and optimization of next-generation indoor wireless networks and for the construction of a digital twin of the building. The need for comprehensive and accurate indoor characterization will be evident in the future hyper-connected mixed real-virtual …

Classification of wireless links using machine learning techniques

Author(s): Gregor Cerar (Author), Mihael Mohorčič (Supervisor), Carolina Fortuna (Co-Supervisor)

Year: 2021

Type: Doctoral dissertation

Due to the nature of the wireless transmission medium, wireless communications are characterised by notably larger losses of data packets than wired communications. The quality of wireless links is highly dependent on channel variations, interference and even transceiver imperfections. Such link uncertainty instigated the development of numerous techniques that can …