In this paper, an augmented crossover memory polynomial model (A-COMPM) is proposed and developed which can be used for characterizing and linearizing multiple-input multiple-output (MIMO) transmitters in the presence of linear and nonlinear crosstalk. The proposed model significantly improves the performance of the crossover memory polynomial model (CO-MPM) by more accurately incorporating the effect of crosstalk. The proposed model performs comparably to the 2 x 2 parallel Hammerstein (2 x 2 PH) model, while requiring the same number of coefficients as CO-MPM and a lower number of coefficients than the 2 x 2 PH. The model was tested for forward modeling and digital predistortion (DPD) applications in the presence of both linear and nonlinear crosstalk. Experimental results show that the model outperforms the CO-MPM and 2 x 2 PH DPDs, at a lower number of coefficients compared to both models. Furthermore, the issue of numerical stability of the DPD

The memory polynomial model is widely used for the behavioural modelling of radio‐frequency non‐linear power amplifiers having memory effects. One challenging task related to this model is the selection of its dimension which is defined by the non‐linearity order and the memory depth. This study presents an approach suitable for the selection of the model dimension in memory polynomial‐based power amplifiers’ behavioural models. The proposed approach uses a hybrid criterion that takes into account the model accuracy and its complexity. The proposed technique is tested on two memory polynomial‐based behavioural models. Experimental validation carried out using experimental data of two Doherty power amplifiers, built using different transistor technologies and tested with two different signals, illustrates consistent advantages of the proposed technique as it significantly reduces the model dimension by more than 60% without compromising its accuracy.

Narrow band interference NBI deteriorates the quality of the spectrum, leading to a poorer performance of modern universal mobile telecommunication system UMTS spread spectrum systems. The linear prediction algorithm is one of the most significant techniques to overcome NBI and enhance the performance of UMTS systems. In this paper, a modified linear prediction algorithm is proposed for NBI suppression in a conditionally stationary environment. This modification improves the error energy estimation in the auto-regression model of the linear prediction. The convergence of the proposed algorithm is evaluated, and its robustness is verified using Kullback-Leibler metrics for conditionally stationary NBI signals. Computer simulations are carried out, and the obtained results demonstrate the performance of the proposed algorithm and its compliance with UMTS protocols. Copyright © 2012 John Wiley & Sons, Ltd.

This study addresses the ill‐conditioning problem of the memory polynomial (MP) model with application to the predistortion of highly non‐linear power amplifiers with memory effects. A resource‐efficient lattice‐based MP structure built using the cascade of a MP generator and a lattice predictor is proposed to overcome the ill‐conditioning of the MP's data matrix. The proposed model performances are benchmarked against those of the MP model as well as the orthogonal MP model. The experimental results demonstrate the suitability of the proposed predistorter as it achieves similar performance in the time and the frequency domains compared to the MP counterpart while alleviating its ill‐conditioning problem.

This study proposes a new technique for the extraction of static non-linearities in wideband transmitters by launching a simple sinusoidal wave within the bandwidth of the system. The transmitter is first characterised under a two-carrier wideband code division multiple access (WCDMA) drive signal and modelled using a memory polynomial model. Two types of memoryless digital predistorters are then synthesised and applied to the amplifier model. The first predistorter is derived from the averaging of the measured data under the two-carrier WCDMA signal, while the second is derived using a sinusoidal wave signal excitation. Discrepancies between the two predistortion functions are illustrated, demonstrating that the predistorter using the averaging technique is biased by the presence of linear memory effects. The results show that the residual distortions at the output of the linearised power amplifier are different and more present when using the sine wave excitation technique compared with the averaging technique. This finding indicates that the sine wave-based technique is more rigorous for de-embedding the static non-linearity from the overall non-linear behaviour, which corroborates the validity of the proposed approach in extracting the true static behaviour of the system and its pertinence for the accurate extraction and quantification of memory effects.

This paper presents an overview of system-level solutions for green wireless communication infrastructure. It illustrates that a combination of high efficiency amplification system with a linearity restoration technique is unavoidable. Currently, Doherty power amplifiers along with digital predistortion technique are able to achieve high power efficiency. However, due to the limited bandwidth of digital predistortion systems (typically 20 MHz), feedforward based linearizers which result in significantly lower power efficiency are still considered for wideband solutions (up to 60 MHz). An experimental approach for extending the bandwidth of digital predistortion systems is reported. This setup is then applied for the linearization, using digital predistortion, of a Doherty power amplifier driven by an 8-carrier WCDMA signal having a total bandwidth of 40 MHz.