Kernel Recursive Least Squares Algorithm for Self-Interference Cancellation in Mobile Communication Transceivers

Beschreibung

Due to the non-ideal components in the analog front-end of frequency division duplex transceivers a part of the transmit signal leaks into the receive path. Together with nonlinear effects in the receiver this leads to self-interferences with possibly high power levels. An important example is the second-order intermodulation distortion (IMD2), since it occurs independently of the transmit carrier frequency. Model based adaptive filtering algorithms are one way to mitigate the IMD2 interference. In this work, we investigate kernel adaptive filters for self interference cancellation, which do not need a model of the specific interference. We focus on a particular variant, the kernel recursive least squares (KRLS). We compare the cancellation performance of this algorithm to a recently published nonlinear adaptive filter that is tailored to the IMD2 problem. It turns out that the KRLS clearly outperforms the model based approach, especially for high transmit power levels.

Zeitraum	02 Nov. 2020
Ereignistitel	Asilomar Conference on Signals, Systems, and Computers
Veranstaltungstyp	Konferenz
Ort	ÖsterreichAuf Karte anzeigen