Cognitive Reconfigurable Embedded Systems Lab
Compact Subsets & Examples
We provide the instructions to download and use the compact subsets. This is the recommended approach to get started with WiSig.
The data can be directly downloaded as zipped files, one file per susbset. Note that the different subsets have some transmitters, receivers, and signals in common, hence, they should not be treated as distinct.
Description: The code provides functions to load the compact datasets. It also includes the code and the weights used to generate the WiSig use cases presented in the paper. A description of the signals in Full WiSig, along with the hardware of each Tx and Rx is also provided.
We provide the instructions to download and use Full WiSig. You are recommended to use Full WiSig only if your requirements are not met using the prepackaged subsets; that is you need more Tx, Rx, or signals. Downloading and using Full WiSig requires more memory and storage than the prepackaged subsets.
Depending whether you want to download the whole Full WiSig or only some files, there a several options
- Whole dataset:
- You can download the zipped version through the links directly. Pro: Smaller download size. Con: The zipped data per file is about 8GB, which might need a lot of memory and space to extract.
- You can download the unzipped version. This can be accomplished using google backup and sync by adding the folder to your personal drive, then sync it to your computer. Other google sync utilities can be used (like gdrive, or similar). Pros: No unzipping. Cons: Larger download size
- Partial dataset:
The function create_dataset_impl provides the download size and links for the needed files, which are not on disk. If only a reasonable number of files is needed, it might be better to download them individually instead of the whole dataset.
Description: The code provides solvers to assist the users create a Tx and Rx lists to meet his required parameters. Then it provides a function to specify the missing files to download and then package the required data into a dictionary, which can be stored as pkl file. Afterwards, the provided code for the compact subsets examples can be used.
Raw WiSig contains the data uploaded directly from Orbit testbed. It has a huge size of 1.7 TB. Processing it consists of many steps run manually, which would take a few days to run aside from the large storage required.
The WiSig Raw was uploaded directly from Orbit testbed. The data is stored per receiver. For each receiver, signals from at most 20 Tx are zipped together as a single Tx group. Each Rx has up 9 Tx groups. Note that in the provided google drive folder, there are multiple folders with the same name (google does not automatically merge them into one folder)
To download the data, google backup and sync can be used by adding the folder to your personal drive, then syncing the data to your computer. Other google sync utilities can be used (like gdrive, or similar).
Similarly, a function is provided to provide direct links, if only a subset of the data is needed.
|Download Directory||Total Size|
|WiSig Raw||1.4 TB|
Description: The code provides function to specify the files to download, then extract them. It provides the MATLAB code for packet detection & screening, equalization, then the creation of the pkl files.
We provide the code to replicate the capture setup used by WiSig. Replicating the captures requires at least two WiFi modules (one of which can act as an access point), and a USRP. The code provided assumes three PCs are used, one for each device, with Ubuntu installed.
Description: Provides the code to replicate the WiSig capture for one WiFi Tx, WiFi AP, and USRP Rx.