Switched radio architecture with non-linear frequency-domain estimation for in-band full-duplex communication

Ayar, Hayrettin and Gürbüz, Özgür (2023) Switched radio architecture with non-linear frequency-domain estimation for in-band full-duplex communication. IEEE Transactions on Wireless Communications . ISSN 1536-1276 (Print) 1558-2248 (Online) Published Online First https://dx.doi.org/10.1109/TWC.2023.3293740

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Enabled by Self-interference (SI) cancellation, In-Band Full-duplex (IBFD) communication is promising for wireless systems as it can double spectral efficiency. At high power levels, SI cancellation drops abruptly due to transceivers’ non-linearity, as estimation/cancellation of SI signal with non-linearity is particularly challenging in the presence of the linear SI channel. To resolve this problem, we propose switched IBFD radio architecture along with a frequency-domain non-linear estimation algorithm. In this architecture, during the training phase, proposed non-linear estimation is performed on the SI signal, isolated from linear SI channel. In the cancellation phase, the estimated non-linear signal is provided as a reference to linear SI estimation, followed by linear cancellation. Experiments on a software defined IBFD radio demonstrate that the proposed solution improves linear cancellation by up to 16 dB, existing non-linear cancellation algorithms by up to 13 dB, and SI is reduced to the noise level for almost all power levels. Since the non-linear model needs to be trained once, at power-up, our IBFD solution is not affected from changes in multi-path, while existing schemes require (re)optimization and (re)training of the model. With the same reasoning, proposed non-linear solution has no estimation overhead and complexity is only for non-linear reconstruction.
Item Type: Article
Uncontrolled Keywords: digital self-interference cancellation; in-band full-duplex; neural networks; non-linear self-interference cancellation; self-interference
Divisions: Faculty of Engineering and Natural Sciences
Depositing User: Özgür Gürbüz
Date Deposited: 07 Aug 2023 20:28
Last Modified: 07 Aug 2023 20:28
URI: https://research.sabanciuniv.edu/id/eprint/47547

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