An Augmented Nonlinear LMS for Digital Self-Interference Cancellation in
Full-Duplex Direct-Conversion Transceivers
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by
Zhe Li, Yili Xia, Wenjiang Pei, Kai Wang, Danilo P. Mandic
2017
Abstract
In future full-duplex communications, the cancellation of self-interference
(SI) arising from hardware non-idealities will play an important role in the
design of mobile-scale devices. To this end, we introduce an optimal digital SI
cancellation solution for shared-antenna-based direct-conversion transceivers.
To establish that the underlying widely linear signal model is not adequate for
strong transmit signals, the impact of various circuit imperfections, including
power amplifier (PA) distortion, frequency-dependent I/Q imbalance,
quantization noise and thermal noise, on the performance of the conventional
augmented least mean square (LMS) based SI canceller, is analyzed. In order to
achieve a sufficient signal-to-interference-plus-noise ratio (SINR) when the
nonlinear SI components are not negligible, we propose an augmented nonlinear
LMS based SI canceller for a joint cancellation of both the linear and
nonlinear SI components by virtue of a widely nonlinear model fit. A rigorous
mean and mean square performance evaluation is conducted to justify the
performance advantages of the proposed scheme over the conventional augmented
LMS solution. Simulations on orthogonal frequency division multiplexing
(OFDM)-based wireless local area network (WLAN) standard compliant waveforms
support the analysis.
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