Comparison of Multilateration Using Wi-Fi RSSI and 5G ToA in a High School Scenario

This study explores indoor positioning using wireless technologies, specifically 5G NR and WiFi (2.4GHz and 5GHz) frequencies, applying multilateration techniques, which are used natively in 5G NR, and the KNN supervised learning algorithm. In order to apply these positioning techniques, we will use RSSI value, due to its ease of use in real-life situations, and the Time of Arrival parameters, as this is the value used in the 5G NR integrated positioning protocol, known as LMF. This study compares 5G NR and WiFi positioning accuracy, demonstrating improvements using 5G NR. For this study, the EMSlice simulation solution was chosen, which has been configured to mimic a real high school. The generated measurements have been compared with real samples to check their quality level. This study aims to provide insights into the advantages and limitations of each technology in various indoor scenarios. The findings contribute to the development of reliable indoor positioning systems. The study revealed that the 5G NR FR1 exhibited a positioning accuracy of 2.35m RMSE, in comparison to 2.75m for 2.4 GHz Wi-Fi and 3.80m for 5 GHz Wi-Fi. Combining Time of Arrival (ToA) with RSSI achieves the highest accuracy, with an RMSE of 2.23m.