Version 6 (modified by welsh, 10 years ago) (diff) |
---|
802.11 Reference Design
802.11 Reference Design: Experiment Framework Setup
Quick Start
- Install a suitable Python distribution (may be already be installed on your PC; see below)
- Download the 802.11 Reference Design Python packages and examples from the repository: /ReferenceDesigns/w3_802.11/python
- Choose an example script (warpnet_example_wlan_throughput.py for example)
- Edit the script header to match your setup (IP address of your PC and serial numbers of your WARP nodes)
- Connect ETH_B of each WARP v3 node to the same gigabit Ethernet switch as your PC
- Open a terminal to the directory containing the example script
- Run the script with Python; for example python warpnet_example_wlan_throughput.py
System Requirements
- 802.11 Reference Design: warpnet support was added to the reference design in v0.8.
- Python: the warpnet framework supports both Python 2 (2.7+) and Python 3 (3.3+). No third-party Python packages are required. See the Python recommendations below for more details.
- Connectivity: the framework requires the host PC and every WARP v3 node be connected to a common gigabit Ethernet switch. We recommend you use a dedicated NIC on your PC to avoid superfluous traffic on the experimental network. The WARP v3 nodes must use their ETH B interfaces for wlan_exp.
- WARP v3 hardware: warpnet requires at least one WARP v3 node running the 802.11 Reference Design. The framework supports up to 253 nodes.
Python Versions
The warpnet framework supports Python 2 (2.7.4+) and Python 3 (3.3+). The core warpnet and wlan_exp scripts require only the core Python packages.
We have tested the framework and example scripts using the operating systems and Python distributions listed below.
Mac OS X
Windows:
- Python 2.7.6.2 (64 bit) in WinPython
- Python 3.3.3.2 (64 bit) in WinPython
Useful Packages
- Spyder: this IDE for Python code development is extremely useful when editing code / developing scripts. Besides automatic syntax checking / highlighting, it integrates the python and ipython consoles to allow interactive debug of code.
- ipython: this interactive Python environment is great for testing experiment scripts and exploring experiment results. Many integrated Python distributions (Anaconda, Spyder, WinPython, etc) integrate the ipython shell.
- numpy: Some of the wlan_exp_log examples use numpy 1.7 for processing large arrays of node log entries. numpy is included in many Python distributions. You can check by running this on your command line: python -c "import numpy; print numpy.version.version". This will print a version number if numpy is installed or an error if it is not. Our examples assume numpy 1.7 or later.
- pandas: The pandas library provides some very useful tools for dealing with large datasets, especially those where time is a dimension (like log entries).