PawPrints: Log 4G, 5G KPIs

Experiment Objective

The objective of the experiment is to log 4G and 5G cellular KPIs using Android APIs, on commercial off-the-shelf (COTS) UEs.

PawPrints Android App

PawPrints can log the below KPIs:

4G KPIs:

1. RSRP (dBm)

2. RSRQ (dB)

3. RSSI (dBm)

4. Timing Advance

5. Band numbers (maps to uplink & downlink frequency and bandwidth)

6. Signal strength in dBm and Arbitrary Strength Units

7. Cell Identity and Physical Cell Identity

5G KPIs:

1. CSI RSRP (reported as unavailable by Android APIs as of Sep 2024)

2. CSI RSRQ (reported as unavailable by Android APIs as of Sep 2024)

3. CSI SINR (reported as unavailable by Android APIs as of Sep 2024)

4. SS RSRP (dBm)

5. SS RSRQ (dB)

6. SS SINR (dB)

9. Signal Strength in dBm and Arbitrary Strength Units

Throughput Iperf KPI:

1. Instantaneous throughput (Mbps)

Throughput can be measured on the uplink and/or the downlink, using UDP or TCP.

Steps:

Below are the steps to run an AERPAW experiment involving PawPrints:

1. 1. 1. Prepare AERPAW experiment: 

         1.  From the AERPAW user web-portal, choose a single vehicle and SPN-Android, which is equipped with the proper mounts to hold up to two phones. 

      2. Define the UAV trajectory: 

         1. The experimenter may create a custom UAV trajectory, that obeys the defined constraints and lies within the specified geofence, using QGroundControl. The procedure to create the mission plan containing the UAV trajectory is explained in Section 3.1.2. 

         2. Pre-defined trajectories may also be reused, using mission plans shared in Section 3.1.2.2. In this case, the experimenter the experimenter specifies their chosen mission plan file in the AERPAW Experiment Information Request Form.

      3. Choose IPerf traffic options: 

         1. PawPrints will log all 4G and 5G KPIs by default. 

         2. Additionally, the user may choose to run IPerf traffic. The user can choose between UDP or TCP for Iperf, on the uplink or the downlink.

      4. Move to Testbed: 

         1. PawPrints is currently not supported in emulation mode. So, the experiment can be moved directly to the testbed.

      5. Post-process the logs: 

         1. After obtaining the log from within the /root/Results folder, the user can convert this log to .csv format as follows:

         2. Run the post-processing script as follows:
            python3 log2csv.py <path-to-pawprints-log> -m <mode> -o <output-path>  
            where <output-path> is in .csv format, and <mode> is either pawprints_4G or pawprints_5G

         3. Generate KMLs using akmlGen.py