Kurzo, YannBurg, AndreasBalatsoukas-Stimming, Alexios2019-06-182019-06-182019-06-182018-01-0110.1109/ACSSC.2018.8645295https://infoscience.epfl.ch/handle/20.500.14299/157000WOS:000467845100103In-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.Computer Science, Information SystemsEngineering, Electrical & ElectronicTelecommunicationsComputer ScienceEngineeringphase-noisetext::conference output::conference proceedings::conference paper