Oualid Hammi

Behavioral modeling and predistortion

In this article, a thorough overview of behavioral modeling and predistortion of dynamic nonlinearities in RF PAs and transmitters was presented. The sensitivity of the DUT behavior to the characteristics of the stimulus was reviewed to ensure appropriate conditions for accurate observation. Nearly all state-of-the-art behavioral models were described and their relative performance and complexity discussed. Similarities and specifics of behavioral modeling and digital predistortion were presented. Thereby, digital predistortion can be seen as a behavioral modeling problem for which performance assessment is much more straightforward. For DUT behavioral modeling, there is no comprehensive metric that allows the model performance evaluation while taking into account the model accuracy in predicting all the three components of the DUT behavior (in-band distortion, static nonlinearity and memory effects). Finally, a software digital predistortion solution that enables closed-loop wideband linearization was briefly presented with excellent linearization capabilities when amplifying a 12-carrier 60-MHZ wide WCDMA signal.

A Dual-Input Digitally Driven Doherty Amplifier Architecture for Performance Enhancement of Doherty Transmitters

In this paper, the novel architecture of a dual-input and digitally driven Doherty amplifier is proposed with the aim of improving the performance of gallium-nitride (GaN) Doherty transmitters. In this work, the power efficiency is enhanced by using digital adaptive phase alignment to compensate for performance degradation due to bias and power-dependant phase misalignment between the carrier and peaking branches. For experimental validation, the proposed dual-input digital Doherty power amplifier (PA) was implemented using a 10-W GaN transistor. Measurement results demonstrate that the dual-input Doherty prototype exhibited a power-added efficiency (PAE) higher than 50% over an 8-dB output power back-off (OPBO) range. In comparison with the conventional fully analog Doherty PA, this represents a 10% improvement in PAE over the same OPBO range. Using a one-carrier Worldwide Interoperability for Microwave Access signal with a 7-dB peak-to-average power ratio, the dual-input Doherty PA, with digital adaptive phase alignment applied at the input of its peaking path, achieved a PAE of 57% at an average output power of 37.8 dBm, along with a - 22-dBc adjacent channel power ratio (ACPR). This corresponds to an improvement of 7% in PAE and 1 dB in average output power for the same ACPR level in comparison with a conventional fully analog Doherty PA.

A Compact Envelope-Memory Polynomial for RF Transmitters Modeling With Application to Baseband and RF-Digital Predistortion

In this letter, a compact envelope-memory polynomial based model, suitable for forward and reverse modeling of weakly nonlinear wireless transmitters and power amplifiers (PAs) exhibiting electrical memory effects, is presented. This model is implemented in a complex gain based architecture and takes advantage of the dependency of PA nonlinearity on the magnitude of the input signal. Contrary to conventional memory polynomials, the proposed model can be implemented in baseband, as well as in radio frequency, digital predistorters. A 100-W average power transmitter is used for experimental validation of the forward and reverse models. Both forward and reverse modeling results obtained with the proposed model are comparable to that of the conventional memory polynomial.

An Accurate Complexity-Reduced “PLUME” Model for Behavioral Modeling and Digital Predistortion of RF Power Amplifiers

This paper introduces a new, accurate, and complexity-reduced three-nonlinear-box model that is suitable for the behavioral modeling and digital predistortion (DPD) of power amplifiers (PAs) exhibiting memory effects. This model is composed of a look-up table (LUT), a memory polynomial (MP), and an envelope MP (EMP), which are all connected in parallel, and it is termed as Parallel-LUT-MP-EMP (PLUME). The PLUME models performance is experimentally assessed using a highly nonlinear Doherty PA driven by a multicarrier wideband code division multiple access signal. A comparison is held between the PLUME model and different state-of-the-art models reported in the literature, such as the MP model, the parallel twin nonlinear two-box model, and the generalized MP (GMP) model. The experimental results, in both behavioral modeling and DPD applications, demonstrate that the proposed PLUME model outperforms the first two models. However, it shows the same accuracy as the GMP model but with an approximately 45% reduction in the number of coefficients. This significant decrease in coefficients considerably reduces the model computational complexity. Another comparison of the resources utilized for field programmable gate array implementation of the PLUME model and the GMP model is performed, which reveals that the PLUME model uses much fewer resources than the other model.

Synergetic Crest Factor Reduction and Baseband Digital Predistortion for Adaptive 3G Doherty Power Amplifier Linearizer Design

A novel approach for power amplifier (PA) characterization suitable for single iteration digital predistorter synthesis is proposed. This approach consists of synergetic crest factor reduction and baseband digital predistortion to avoid the average power variation at the input of the PA between the characterization and linearization steps. This is achieved by bypassing the crest factor reduction block during the characterization step and by applying it concurrently with digital predistortion in the linearization step. First, the PAs behavior sensitivity to the average input power is evaluated. The limitations of conventional approaches for the PA characterization, in the context of single iteration digital predistortion, are then demonstrated. The performance of the proposed technique is validated experimentally on a 300-W peak PA. The measured improvement of the adjacent channel power ratio at the output of the linearized amplifier is 16 dBc for the conventional approach and 29 dBc for the proposed approach.

Metrics and Methods for Benchmarking of RF Transmitter Behavioral Models With Application to the Development of a Hybrid Memory Polynomial Model

This paper presents a study of performance evaluation metrics for behavioral models of power amplifiers and transmitters. A novel normalized absolute mean spectrum error criterion is proposed as a performance evaluation metric along with a method for accurate benchmarking of behavioral models and their ability to predict the in-band response, static nonlinearity, and memory effects of the device under test. The proposed metric and method are validated with a study of different memory polynomial based models, focusing on the model accuracy, complexity, and identification robustness. This experimental validation highlights the robustness of the proposed metric and its ability to accurately quantify the performance of several behavioral models in predicting the static nonlinearity and memory effects of the device under test for several test conditions. In addition, the results of the comparative study between the memory polynomial models are used to propose a hybrid memory polynomial model. The superiority of the proposed model is assessed by comparing its performance to that of the studied memory polynomial models.

Systematic and Adaptive Characterization Approach for Behavior Modeling and Correction of Dynamic Nonlinear Transmitters

This paper proposes a comprehensive and systematic characterization methodology that is suitable for the forward and reverse behavior modeling of wireless transmitters (Txs) driven by wideband-modulated signals. This characterization approach can be implemented in adaptive radio systems since it does not require particular signal or training sequences. The importance of the nature of the driving signal and its average power on the behavior of radio-frequency Txs are experimentally investigated. Critical issues related to the proposed characterization approach are analytically studied. This includes a new delay-estimation method that achieves good accuracy with low computational complexity. In addition, the receiver linear calibration and its noise budget are investigated. To demonstrate the accuracy and robustness of the proposed method, a full characterization (including the memoryless nonlinearity and the memory effects) of a 100-W Tx driven by a multicarrier wideband code-division multiple-access signal is carried out, and its forward and reverse models are identified. Cascading the identified reverse model derived using the proposed methodology and the Tx prototype leads to excellent compensation of the static nonlinearities and the memory effects exhibited by the latter. Critical issues in implementing this approach are also discussed.

On the Robustness of Digital Predistortion Function Synthesis and Average Power Tracking for Highly Nonlinear Power Amplifiers

In this paper, a comprehensive study of the robustness of the digital predistortion function synthesis is presented. This study covers two aspects: the processing of the power amplifier (PA) input and output measured data intended for the extraction of the corresponding predistortion function, and the optimal setting of the predistorters small-signal gain to adaptively track the average power variation between the input and output of the pre-distorter. First, the accuracy of the polynomial curve fitting and the lookup tables scheme in mimicking the measured AM/AM and AM/PM characteristics of the PA is investigated. To address the high dispersion of coefficients of the polynomial function, which limits the order that can be implemented and the fitting capabilities, a pre-processing technique is proposed. Second, the fitted PA curves are used to investigate the effects of the small-signal gain of the predistortion function on the linearization performance. An automated average power tracking technique is introduced in order to maintain a unit average gain of the predistorter. The measured spectra at the output of the amplifier show an additional 12-dBc improvement in the output spectrum regrowth.

Power Amplifiers' Model Assessment and Memory Effects Intensity Quantification Using Memoryless Post-Compensation Technique

A novel approach for power amplifiers static nonlinearity characterization in the presence of memory effects is presented. A subsampling technique is used to reduce the bandwidth of the test signal without changing the waveform characteristics. This cancels the memory effects of the amplifier without affecting its static behavior. Memoryless AM/AM and AM/PM characteristics are measured as a function of the carrier frequency. This points out the contribution of the frequency dependency of the amplifiers static nonlinearity to its behavior under wideband signal drive. A memoryless post-compensation technique is then introduced to accurately assess the performance of several behavioral models. In fact, it is demonstrated that direct comparison of the measured output of the device-under-test with the estimated output does not provide reliable assessment of the model performance. Conversely, memoryless post-compensation efficiently differentiates the performance of these models. To provide a comprehensive approach for model validation and prototype performance evaluation, memory effects intensity metrics are introduced. These metrics are applied to evaluate the memory effects present in a 300-W peak power Doherty amplifier driven by various multicarrier wideband code division multiple access signals.

Power Alignment of Digital Predistorters for Power Amplifiers Linearity Optimization

In this paper, a study of the power alignment issue in digital predistorters is presented. The proper alignment is achieved by adjusting the normalization gain used to synthesize the predistortion function. The dependencies of the linearity and power efficiency of the linearized amplifier upon the gain normalization factor are investigated, and it is shown that the efficiency of the linearized amplifier is almost unaffected by variation of the normalization gain. Conversely, the linearity performance of the linearized power amplifier is found to be dependent on the gain normalization factor, as a consequence of the average power variation through the predistorter. Indeed, the proper power alignment of the predistorter following an adequate choice of the normalization gain shows a significant improvement in the measured adjacent channel power ratio at the linearized amplifier output.