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A Python application for Linux machines to perform WiFi site surveys and present the results as a heatmap overlayed on a floorplan

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python-wifi-survey-heatmap

Project Status: Inactive – The project has reached a stable, usable state but is no longer being actively developed; support/maintenance will be provided as time allows. Docker Hub Build Status

A Python application for Linux machines to perform WiFi site surveys and present the results as a heatmap overlayed on a floorplan.

This is rather rough "beta" code. The heatmap generation code is roughly based on Beau Gunderson's MIT-licensed wifi-heatmap code.

Many thanks to DL6ER who contributed a massive amount of improvements to this project.

Operating System support

As mentioned in the description, this project is for LINUX ONLY. That doesn't mean a Linux docker container on Windows or Mac, or running it on Mac. The WiFi features - the heart of this project - are built on libnl3, a Python wrapper around the Netlink protocol-based Linux kernel interfaces. In short, the survey commands will only work on a system that's running Linux, and where the Linux kernel is directly managing the WiFi hardware.

For people not running Linux, I am aware of (but have no affiliation with, haven't used, and can't endorse) the following projects:

Quick start

Check out the Running In Docker steps below to get single-line commands that run without the need to install anything on your computer (thanks to using docker). Creating a heatmap using the software consists of the following three essential steps:

  1. Start an iperf3 server on any machine in your local network. This server is used for bandwidth measurements to be independent of your Internet connection. When omitting the --server option, this may be skipped, however, be aware that the performance heatmaps tpyically are the icing on the cake of your measurement and are very useful in determining the real performance of your WiFi.
  2. Use the wifi-survey tool to record a measurement. You can load a floorplan and click on your current location ot record signal strength and determine the achievable bandwidth.
  3. Once done with all the measurements, use the wifi-heatmap tool to compute a high-resolution heatmap from your recorded data. In case your data turns out to be too coarse, you can always go back to step 2 and delete or move old and also add new measurements at any time.

Installation and Dependencies

NOTE: These can all be ignored when using Docker. DOCKER IS THE RECOMMENDED INSTALLATION METHOD. See below.

  • The Python iperf3 package, which needs iperf3 installed on your system.
  • The Python libnl3 package.
  • wxPython Phoenix, which unfortunately must be installed using OS packages or built from source.
  • An iperf3 server running on another system on the LAN, as described below is recommended but optional.

Recommended installation is via python setup.py develop in a virtualenv setup with --system-site-packages (for the above dependencies).

Tested with Python 3.7.

Data Collection

At each survey location, data collection should take 45-60 seconds. The data collected is currently:

  • 10-second iperf3 measurement, TCP, client (this app) sending to server, default iperf3 options [optional, enable with --server]
  • 10-second iperf3 measurement, TCP, server sending to client, default iperf3 options [optional, enable with --server]
  • 10-second iperf3 measurement, UDP, client (this app) sending to server, default iperf3 options [optional, enable with --server]
  • Recording of various WiFi details such as advertised channel bandwidth, bitrate, or signal strength
  • Scan of all visible access points in the vicinity [optional, enable with --scan]

Hints: - The duration of the bandwidth measurement can be changed using the --duration argument of wifi-survey. This has great influence on the actual length of the individual data collections. - Scanning for other network takes rather long. As this isn't required in most cases, it is not enabled by default

Usage

Server Setup

On the system you're using as the iperf3 server, run iperf3 -s to start iperf3 in server mode in the foreground. By default it will use TCP and UDP ports 5201 for communication, and these must be open in your firewall (at least from the client machine). Ideally, you should be running the same exact iperf3 version on both machines.

Performing a Survey

The survey tool (wifi-survey) only requires root privileges for scans. It can be run via sudo in which case it will drop back to your user after forking off the scan process, or it will launch the scan process via pkexec if not started with sudo (or via Docker; see below).

First connect to the network that you want to survey. Then, run sudo wifi-survey where:

Command-line options include:

  • -i INTERFACE / --interface INTERFACE is the name of your Wireless interface (e.g. wlp3s0)
  • -p PICTURE / --picture PICTURE is the path to a floorplan PNG file to use as the background for the map; see examples/example_floorplan.png for an example. In order to compare multiple surveys it may be helpful to pre-mark your measurement points on the floorplan, like `examples/example_with_marks.png <examples/example_with_marks.png`_. The UI currently loads the PNG at exact size, so it may help to scale your PNG file to your display.
  • -t TITLE / --title TITLE is the title for the survey (such as the network name or AP location), which will also be used to name the data file and output files.
  • -s IPERF3_SERVER / --server IPERF3_SERVER to enable iperf3 scans. The generated speed heatmaps are very useful (much more useful than signal strength) in visualizing the real performance of your network as they are live measurements with real data (instead of only theoretical values).
  • -S / --scan to enable wireless scaning at the end of each measurement. This may take a lot of time, however, generates data used later for generating channel utilization graphs. If you're using a modern wireless product that allows running RF scans, it makes sense to use that data instead of these scans.
  • -b BSSID / --bssid BSSID allows you to specify a single desired BSSID for your survey. This will be checked several times during of every measurement, and the measurement will be discarded if you're connected to the wrong BSSID. This can be useful as a safeguard to make sure you don't accidentally roam to a different AP.
  • -d 123 / --duration 123 allows you to change the duration of each individual iperf3 test run (default is 10 seconds as mentioned above)
  • --ding FILENAME will play the audio file at FILENAME when each measurement point is complete. See Playing A Sound When Measurement Finishes below for details.

If TITLE.json already exists, the data from it will be pre-loaded into the application; this can be used to resume a survey.

When the UI loads, you should see your PNG file displayed. The UI is really simple:

  • If you (left / primary) click on a point on the PNG, this will begin a measurement (survey point). The application should draw a yellow circle there. The status bar at the bottom of the window will show information on each test as it's performed; the full cycle typically takes a minute or a bit more. When the test is complete, the circle should turn green and the status bar will inform you that the data has been written to Title.json and it's ready for the next measurement. If iperf3 encounters an error, you'll be prompted whether you want to retry or not; if you don't, whatever results iperf was able to obtain will be saved for that point.
  • The output file is (re-)written after each measurement completes, so just exit the app when you're finished (or want to resume later; specifying the same Title will load the existing points and data from JSON).
  • Right (secondary) clicking a point will allow you to delete it. You'll be prompted to confirm.
  • Dragging (left/primary click and hold, then drag) an existing point will allow you to move it. You'll be prompted to confirm. This is handy if you accidentally click in the wrong place.

At the end of the process, you should end up with a JSON file in your current directory named after the title you provided to wifi-survey (Title.json) that's owned by root. Fix the permissions if you want.

Note: The actual survey methodology is largely up to you. In order to get accurate results, you likely want to manually handle AP associations yourself. Ideally, you lock your client to a single AP and single frequency/band for the survey.

Playing A Sound When Measurement Finishes

It's possible to have wifi-survey play a sound when each measurement is complete. This can be handy if you're reading or watching something in another window while waiting for the measurements.

To enable this, call wifi-survey with the --ding argument, passing it the path to an audio file to play. A short sound effect is included in this repository at wifi_survey_heatmap/complete.oga and can be used via --ding wifi_survey_heatmap/complete.oga. by default, this will call /usr/bin/paplay (the PulseAudio player) passing it the ding file path as the only argument. The command used can be overridden with --ding-command /path/to/command but it must be one that accepts the path to an audio file as its only argument. If you launch the scan as your user or via sudo, the UI & the PulseAudio client will be run as your user and work without further configuration. If you run as root not via sudo, then additional PuseAudo configuration may be necessary.

Inside Docker, however, this becomes quite a bit more difficult. Currently PulseAudio systems are supported, and this can be set up and enabled with the following steps:

1. Find your host computer's IP address on the docker0 network: ip addr show dev docker0 - mine (and most Linux machines) is 172.17.0.1 1. Find the CIDR block of your docker0 network. I do this using ip route show dev docker0, which gives me a CIDR of 172.17.0.0/16 1. Have PulseAudio listen on a TCP socket, allowing connections from your Docker network: pactl load-module module-native-protocol-tcp port=34567 auth-ip-acl=172.17.0.0/16 1. If you have iptables restricting traffic, insert a rule allowing traffic on port 34567 from Docker before your DROP rule. For example, to insert a rule at position 5 in the INPUT chain: iptables -I INPUT 5 -s 172.17.0.0/16 -p tcp -m multiport --dports 34567 -m comment --comment "accept PulseAudio port 34567 tcp from Docker" -j ACCEPT 1. When running the Docker container, add -e "PULSE_SERVER=tcp:172.17.0.1:34567" to the docker run command. 1. When running wifi-survey, add the --ding argument as specified above. Note that the path to the file must be inside the container; you can put an audio file in your current directory and use it via --ding /pwd/audioFile or you can use the default file built-in to the container via --ding /app/wifi_survey_heatmap/complete.oga

Heatmap Generation

Once you've performed a survey with a given title and the results are saved in Title.json, run wifi-heatmap TITLE to generate heatmap files in the current directory. This process does not require (and shouldn't have) root/sudo and operates only on the JSON data file. For this, it will look better if you use a PNG without the measurement location marks.

You can optionally pass the path to a JSON file mapping the access point MAC addresses (BSSIDs) to friendly names via the -a / --ap-names argument. If specified, this will annotate each measurement dot on the heatmap with the name (mapping value) and frequency band of the AP that was connected when the measurement was taken. This can be useful in multi-AP roaming environments.

The end result of this process for a given survey (Title) should be some .png images in your current directory:

  • channels24_TITLE.png - Bar graph of average signal quality of APs seen on 2.4 GHz channels, by channel. Useful for visualizing channel contention. (Based on 20 MHz channel bandwidth)
  • channels5_TITLE.png - Bar graph of average signal quality of APs seen on 5 GHz channels, by channel. Useful for visualizing channel contention. (Based on per-channel bandwidth from 20 to 160 MHz)
  • signal_quality_TITLE.png - Heatmap based on the received signal strength.
  • tx_power_TITLE.png - Heatmap based on the transmitter power your WiFi card used. If your WiFi card doe snot support adaptive power management, this number will stay constant.
  • tcp_download_Mbps_TITLE.png - Heatmap of iperf3 transfer rate, TCP, downloading from server to client.
  • tcp_upload_Mbps_TITLE.png - Heatmap of iperf3 transfer rate, TCP, uploading from client to server.
  • udp_download_Mbps_TITLE.png - Heatmap of iperf3 transfer rate, UDP, downloading from server to client.
  • udp_upload_Mbps_TITLE.png - Heatmap of iperf3 transfer rate, UDP, uploading from client to server.
  • jitter_download_TITLE.png - Heatmap based on UDP jitter measurement in milliseconds.
  • jitter_upload_TITLE.png - Heatmap based on UDP jitter measurement in milliseconds.
  • frequency_TITLE.png - Heatmap of used frequency. May reveal zones in which Wi-Fi steering moved the device onto a different band (2.4GHz / 5 GHz co-existance).
  • channel_bitrate_TITLE.png - Heatmap of negotiated channel bandwidth

If you'd like to synchronize the colors/thresholds across multiple heatmaps, such as when comparing different AP placements, you can run wifi-heatmap-thresholds passing it each of the titles / output JSON filenames. This will generate a thresholds.json file in the current directory, suitable for passing to the wifi-heatmap -t / --thresholds option.

Add --show-points to see the measurement points in the generated maps. Typically, they aren't important when you have a sufficiently dense grid of points so they are hidden by default.

Running In Docker

Survey

Note the

docker run \
  --net="host" \
  --privileged \
  --name survey \
  -it \
  --rm \
  -v $(pwd):/pwd \
  -w /pwd \
  -e DISPLAY=$DISPLAY \
  -v "$HOME/.Xauthority:/root/.Xauthority:ro" \
  jantman/python-wifi-survey-heatmap \
  wifi-survey -b <BSSID> -i <INTERFACE> -s <IPERF SERVER> -p <FLOORPLAN PNG> -t <TITLE>

Note that running with --net="host" and --privileged is required in order to manipulate the host's wireless interface.

Heatmap

docker run -it --rm -v $(pwd):/pwd -w /pwd jantman/python-wifi-survey-heatmap:23429a4 wifi-heatmap <TITLE>

iperf3 server

Server: docker run -it --rm -p 5201:5201/tcp -p 5201:5201/udp jantman/python-wifi-survey-heatmap iperf3 -s

Examples

Floorplan

example floorplan image

Floorplan with Measurement Marks

example floorplan image with measurement marks

2.4 GHz Channels

example 2.4 GHz channel usage

5 GHz Channels

example 5 GHz channel usage

Jitter

example jitter heatmap

Quality

example quality heatmap

RSSI / Signal Strength

example rssi heatmap

TCP Download Speed (Mbps)

example tcp download heatmap

TCP Upload Speed (Mbps)

example tcp upload heatmap

UDP Upload Speed (Mbps)

example udp upload heatmap

Issues

If you see:

Couldn't connect to accessibility bus: Failed to connect to socket /run/user/1000/at-spi/bus_0: No such file or directory

when running in docker, mount the socket in docker explicitly by adding an additional -v switch:

docker run ... -v /run/user/1000/at-spi/bus_0:/run/user/1000/at-spi/bus_0 ...

Release Process

  1. Merge all PRs desired in the release.
  2. Update CHANGES.rst, commit, push.
  3. Tag the repo with the version number and push. GitHub Actions will build and push the Docker image and create a Release.