Driving-Wild

LTE, SA-5G, NSA-5G Driving Experiments

This folder contains the dataset, processing and plotting scripts for LTE, SA-5G, NSA-5G Driving experiments conducted using T-Mobile. It covers Figure 9 referenced in Section 3.2 of the paper.

Note that we don't have access to RRC messages to accurately determine the handoff event, so we use Samsung Service Code *#0011#* to watch the screen and map the handoff events with the overlaid clock app built by us. We also provide a few sample video recordings of the experiment which can be found here. Using these video recordings, we can verify the handoff events for a run.

Run the following command to generate plots.

python3 plot-section3-figure9.py

Folder Structure

Filename	Description
data/[Device ID]-[run number]-handoff.csv	Logs containing handoff information collected using Samsung Service Code
data/[Device ID]-[run number]_PM.csv	Power logs collected using Monsoon Power Monitor
data-processed/[run number].csv	Processed logs generated after merging power and handoff logs. See the Dataset Description section for more details
Process-Logs.py	Python script to process handoff and power logs
plot-section3-figure9.py	Python script to generate Figure 9 in the paper. See the Generating Plots section for more details

Dataset Description

Field Name	Description
time	Time elapsed since the start of experiment (sec)
avg_power	Average power during each second (W)
active interface	Mobile network the device is connected to [ NSA-5G, SA-5G, 4G(LTE) ]
handover type	Handover type [ 4t4: (4G to 4G horizontal handover), 4t5: (4G to 5G vertical handover), 5t4: (5G to 4G vertical handover), 5t5: (5G to 5G horizontal handover) ]

Generating Plots

The scripts will generate Figure 9.

Requirements

Here are the software/package requirements. The version number in the bracket indicates the minimum version that our script has been tested on.

• Python 3 (3.7.7 and higher)
• Pandas (1.1.3 and higher)
• Matplotlib (3.3.1 and higher)

Running code

To regenerate the processed logs, the following command can be used.

python3 Process-Logs.py

The processed logs will be placed in data-processed folder. The Dataset Description section gives an overview of the data generated after processing raw logs.

To generate Figure 9 shown in the paper, simply run the following command

python3 plot-section3-figure9.py

This will create a plots folder having figures in 3 formats (png, pdf and eps).