# WiFi FTM, UWB and Cellular-Based Radio Fusion for Indoor Positioning
## 4 Experimental Setup  
In this section, an experimental setup for validating the solution is described. To validate the benefits of the proposed solution with real data, an UWB and a WiFi FTM deployment are used as high-precision ranging technologies and an indoors LTE network as a backup element with low-location accuracy and high availability. LTE is used as a placeholder of 5G due to the lack of an experimental infrastructure, but the conclusions of the experiment are expected to be similar with femtocells in a height of 3.5 m. The LTE network belongs to the University of Malaga which has configured the network to reduce the interferences with commercial networks. On the other hand, according to the multi-path effects, the scenario is a laboratory which presents several metallic elements, such as computers, shelves, etc. Therefore, we expect that the measurements are heavily affected by multipath. The UWB deployment is based on Decawave DWM1000 devices (DecaWave, Dublin, Ireland) and they were placed on top of shelves in order to cover the whole scenario with good visibility (2 m height). Meanwhile, the WiFi FTM APs are Google WiFi mesh routers (Google, Montain View, CA, USA) that were placed in typical places for providing WiFi connectivity throughout the laboratories (1 m height). Both DWM1001 and Google WiFi routers are set to their default configuration parameters [33; 34]. The UWB devices transmit with a power of \(-14.3\) dBm and they are centered in 6 GHz [34]. The Google WiFi routers are configured to work at 2.4 GHz and, to the best of our knowledge, the WiFi  
Figure 2: Functionality of the MLE during a real experiment. RTT FTM function could not operate at 5 GHz. The transmission power of the router is by default 28.17 dBm [33]. The LTE station parameters are configured with a transmission power of \(-6.8\) dBm and downlink and uplink frequencies of 2630 MHz and 2510 MHz, respectively. The location target device is a Google Pixel 3 which runs Android 9.0 and supports WiFi FTM RTT. An application has been programmed to capture all the ranging data from the network reference points: LTE base stations, UWB anchors and WiFi APs. The ranges with the LTE stations are estimated using the measured RSSI which is modelled by the indoor office propagation model [35]. The WiFi FTM ranges are obtained from an API created for this work. For the UWB measurements, a DWM1000 device is attached to the smartphone and connected via Bluetooth low energy (BLE) to read the UWB data. A limitation on the performance of the UWB devices is that the UWB tag can only receive the information of four anchors simultaneously due to the software provided with the DWM1000 family products [4]. The implementation of the positioning and networking stack (PANS) firmware, the two-way ranging (TWR) communication protocol and the data frame limit the number of anchors that the tag can listen at the same time. Hence, despite a high-density set-up, the system is not highly over-determined. The captured data are sent to a Flask server with a MySQL database which is configured in a laptop(Lenovo, Beijing, China) running Windows 10. The sampling rate is 1 Hz. The measurements are timestamped with the global satellite system (GPS) clock as a time reference. The measurements are captured in a reduced time interval, assuming simultaneous samples which would introduce some error due to synchronisation. However, a regular user moves slowly in indoor scenarios which can lead to a maximum error of a few centimetres of ranging information. Additionally, we have set the height of the phone to 1.1 m of height simulating a person is carrying the phone on his pocket. Then, we send the information to the Flask server to process the localisation data via HTTP with no retransmission allowed in order to maintain the experiments as real-time. These experiments were performed in three laboratories and hallways with a very limited vision of the sky. Figure 3 illustrates the three experimental cases that have been measured in the two different scenarios.