==== Introduction
RF canceller tuning is an integral problem in enabling the functionality of full-duplex radios. However, very few people have access to hardware to experiment with and validate RF canceller tuning algorithms.  We provide a dataset of RF canceller performance across multiple indoor and outdoor locations to enable anyone to experiment with methods for real time canceller tuning.

This dataset is associated with our work published in WiNTECH 2025. Please cite our work if you use it.
K. Hermstein, A. Kwak, M. Kohli, and G. Zussman, “Real-time RF canceler tuning in practical full-duplex radios,” in Proc. ACM MobiCom’25 Workshop on Wireless Network Testbeds, Experimental evaluation & CHaracterization (WiNTECH’25), 2025.

==== Phase and Amplitude Based Canceller Performance Dataset
This dataset contains the performance of the P&A-based canceller across numerous environments. Data collections are still underway. There are preliminary collections below.

Dataset 1: Canceller performance across 30 environments

- This dataset contains the canceller performance across 30 environments. For each location, we provide a triplet of the self-interference channel estimate (CSI), residual self-interference (RSI) across all configurations, and the optimal configuration (attenuation and phase setting).
- Each triplet is a Python dictionary with keys "csi", "rsi", "opt_cfg" saved as a .pkl file that can be read with the pickle Python package.