Samenvatting
The fundamental challenge in full-duplex (FD) communications is to cancel the strong self-interference (SI) signal. SI cancellation is usually implemented by a combination of passive SI cancellation, active analog SI cancellation, and active digital SI cancellation. A part of the SI cancellation needs to be carried out in the analog domain to avoid saturating the analog front-end of the receiver, but digital cancellation is generally easier to implement using DSP circuits. Polynomial models are often used in practice to model transceiver non-linearities, but they typically have a very large number of trainable parameters which translates into a high computational complexity. More recently, various machine learning methods have been successfully used to perform non-linear digital SI cancellation as a lower- complexity alternative to polynomial models. However, in all of the aforementioned works the SI cancellation and the signal-of- interest detection are treated independently. In this work, we propose to use a neural network for joint detection and nonlinear SI cancellation. Preliminary experimental results with a measured dataset from a full-duplex testbed show that this joint approach can provide bit-error rate improvements of 1 to 3 dB. We also discuss some limitations of our current method and we outline directions for future research.
Originele taal-2 | Engels |
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Titel | 2021 55th Asilomar Conference on Signals, Systems, and Computers |
Redacteuren | Michael B. Matthews |
Uitgeverij | Institute of Electrical and Electronics Engineers |
Pagina's | 989-992 |
Aantal pagina's | 4 |
ISBN van elektronische versie | 978-1-6654-5828-3 |
DOI's | |
Status | Gepubliceerd - 4 mrt. 2022 |
Evenement | 55th Asilomar Conference on Signals, Systems and Computers, ACSSC 2021 - Virtual, Pacific Grove, Verenigde Staten van Amerika Duur: 31 okt. 2021 → 3 nov. 2021 Congresnummer: 55 |
Congres
Congres | 55th Asilomar Conference on Signals, Systems and Computers, ACSSC 2021 |
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Verkorte titel | ACSSC |
Land/Regio | Verenigde Staten van Amerika |
Stad | Pacific Grove |
Periode | 31/10/21 → 3/11/21 |
Bibliografische nota
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