@article{Li:2018:10.1109/TSP.2018.2846250,
author = {Li, Z and Xia, Y and Pei, W and Wang, K and Mandic, D},
doi = {10.1109/TSP.2018.2846250},
journal = {IEEE Transactions on Signal Processing},
pages = {4065--4078},
title = {An Augmented Nonlinear LMS for Digital Self-Interference Cancellation in Full-Duplex Direct-Conversion Transceivers},
url = {http://dx.doi.org/10.1109/TSP.2018.2846250},
volume = {66},
year = {2018}
}

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TY  - JOUR
AB  - In future full-duplex communications, the cancellation of self-interference (SI) arising from hardware nonidealities 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 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 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-based wireless local area network standard compliant waveforms support the analysis.
AU  - Li,Z
AU  - Xia,Y
AU  - Pei,W
AU  - Wang,K
AU  - Mandic,D
DO  - 10.1109/TSP.2018.2846250
EP  - 4078
PY  - 2018///
SN  - 1053-587X
SP  - 4065
TI  - An Augmented Nonlinear LMS for Digital Self-Interference Cancellation in Full-Duplex Direct-Conversion Transceivers
T2  - IEEE Transactions on Signal Processing
UR  - http://dx.doi.org/10.1109/TSP.2018.2846250
UR  - http://hdl.handle.net/10044/1/60779
VL  - 66
ER  - 

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