In-band full-duplex systems are able to transmit and receive information simultaneously on the same frequency band. Due to the strong self-interference caused by the transmitter to its own receiver, the use of non-linear digital self-interference cancellation is essential. In this work, we present a hardware architecture for a neural network based non-linear self-interference canceller and we compare it with our own hardware implementation of a conventional polynomial based canceller. We show that, for the same cancellation performance, the neural network canceller has a significantly higher throughput and requires fewer hardware resources.
@article{arxiv.1812.00449,
title = {Design and Implementation of a Neural Network Aided Self-Interference Cancellation Scheme for Full-Duplex Radios},
author = {Yann Kurzo and Andreas Burg and Alexios Balatsoukas-Stimming},
journal= {arXiv preprint arXiv:1812.00449},
year = {2018}
}
Comments
Presented at the Asilomar Conference for Signals, Systems, and Computers