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In this paper, we present a class of cascaded nonlinear models for complex-valued system identification, aimed at baseband modeling of nonlinear radio systems. The proposed models consist of serially connected elementary linear and nonlinear blocks, with the nonlinear blocks implemented as uniform spline-interpolated look-up tables (LUT) and the linear blocks as FIR filters. Wiener, Hammerstein, and Wiener-Hammerstein models are built, and simple but efficient gradient based adaptive learning rules are derived for all the models. This approach leads to remarkably simple solutions in terms of computational complexity, making the techniques suitable for real-time implementation. The proposed methods are then applied to full-duplex self-interference cancellation and digital predistortion in various real-life scenarios. First, evaluations with measured data from an in-band full-duplex prototype working at 2.4 GHz ISM band show that the algorithms are capable of obtaining similar cancellation performance as existing state-of-the-art solutions, regardless of the clearly reduced complexity. Second, a mmW active antenna array working at 28 GHz center frequency is digitally predistorted with the proposed solutions. The unwanted emissions and nonlinear distortion are suppressed to similar levels as with other state-of-the art solutions, and the corresponding linearity specifications are fulfilled in all cases, while the processing complexity is again drastically reduced. [ABSTRACT FROM AUTHOR]

This paper presents a novel digital self-interference canceller for an inband multiple-input-multiple-output (MIMO) full-duplex radio. The signal model utilized by the canceller is capable of modeling the in-phase quadrature (IQ) imbalance, the nonlinearity of the transmitter power amplifier, and the crosstalk between the transmitters, thereby being the most comprehensive signal model presented thus far within the full-duplex literature. Furthermore, it is also shown to be valid for various different radio frequency (RF) cancellation solutions. In addition to this, a novel complexity reduction scheme for the digital canceller is also presented. It is based on the widely known principal component analysis, which is used to generate a transformation matrix for controlling the number of parameters in the canceller. Extensive waveform simulations are then carried out, and the obtained results confirm the high performance of the proposed digital canceller under various circuit imperfections. The complexity reduction scheme is also shown to be capable of removing up to 65% of the parameters in the digital canceller, thereby significantly reducing its computational requirements. [ABSTRACT FROM AUTHOR]