Tipo di tesi
Tesi di laurea magistrale
Titolo
Deep Learning-based MIMO Indoor Positioning
Dipartimento
INGEGNERIA DELL'INFORMAZIONE
Corso di studi
COMPUTER ENGINEERING
Parole chiave
- Channel
- CNN
- Colab
- Convolutional
- Deep
- Indoor
- Learning
- MIMO
- Neural
- Positioning
- Tensorflow
- Wireless
Data inizio appello
21/02/2020
Riassunto (Italiano)
In this work a deep convolutional neural network was trained, with the purpose of indoor positioning. Starting from a MIMO propagation model, expressing wireless channel response as function of 3-dimensional position coordinates, a specific CNN have been trained. This was then tested with data coming from a real scenario. Furthermore, a dedicated CNN was trained considering this dataset, in order to compare perfomances with the previous one. Finally, an hybrid approach was provided: the amount of data coming from real scenario was expanded with gradually increasing portions of data generated from propagation model. A dedicated CNN was trained also in this case to evaluate overall performances.
