Support Vector Machines For Self-Interference Cancellation in Mobile Communication Transceivers
Sprache des Vortragstitels:
Vehicular Technology Conference
Sprache des Tagungstitel:
In frequency division duplex transceivers, a part of the transmit signal leaks into the receive path due to the non-ideality of the analog duplexer. Although operating on a different frequency band, non-ideal effects in the receive path lead to self-interferences with potentially higher power level than the wanted receive signal. One option to tackle this problem is the use of adaptive filtering algorithms for interference cancellation. In this work, we discuss support vector machines (SVMs) as an alternative approach. Different to the existing methods, the proposed concept does not need a model of the type of interference. We investigate the cancellation performance of SVMs compared to a recently published nonlinear adaptive filter for a specific type of interference called the second-order intermodulation distortion. It turns out that SVMs clearly outperform the adaptive filtering approach even for the severe case of narrow allocated transmit signals and high transmit power levels.