Deep Learning Approach for LOS and NLOS Identification in the Indoor Environment

Autor: Alicja Olejniczak, Piotr Rajchowski, Krzysztof Cwalina, Olga Blaszkiewicz, Jarosław Sadowski
Rok vydání: 2020
Předmět:
Zdroj: 2020 Baltic URSI Symposium (URSI).
DOI: 10.23919/ursi48707.2020.9253757
Popis: Due to confined spaces and various obstacles e.g. walls, furniture, indoor environment may be considered as a harsh and disturbing in terms of the indoor radiocommunication services operation. The given paper presents FNN (Feedforward Neural Network) method for LOS (Line-Of-Sight) and NLOS (Non-Line-Of-Sight) identification which may support mitigation of such a negative influence. Described FNN architecture was evaluated based on a real indoor measurements collected with the use of the UWB (Ultra Wideband) radio modules.
Databáze: OpenAIRE