A comparative study of state-of-the-art behavioral models for microwave power amplifiers (PAs) is presented in this paper. After establishing a proper definition for accuracy and complexity for PA behavioral models, a short description on various behavioral models is presented. The main focus of this paper is on the modeling accuracy as a function of computational complexity. Data is collected from measurements on two PAs-a general-purpose amplifier and a Doherty PA designed for WiMAX-for different output power levels. The models are characterized in terms of accuracy and complexity for both in-band and out-of-band error. The results show that, among the models studied, the generalized memory polynomial behavioral model has the best tradeoff for accuracy versus complexity for both PAs, and can obtain high performance at half of the computational cost of all other models analyzed.

https://publications.lib.chalmers.se/records/fulltext/local_121905.pdf

A Comparative Analysis of the Complexity/Accuracy Tradeoff in Power Amplifier Behavioral Models

A new behavioral model for digital predistortion of radio frequency (RF) power amplifiers (PAs) is proposed in this paper. It is derived from a modified form of the canonical piecewise-linear (CPWL) functions using a decomposed vector rotation (DVR) technique. In this model, the nonlinear basis function is constructed from piecewise vector decomposition, which is completely different from that used in the conventional Volterra series. Theoretical analysis has shown that this model is much more flexible in modeling RF PAs with non-Volterra-like behavior, and experimental results confirmed that the new model can produce excellent performance with a relatively small number of coefficients when compared to conventional models.

https://researchrepository.ucd.ie/bitstream/10197/8424/1/TMTT-2014-09-0998_Final.pdf

Decomposed Vector Rotation-Based Behavioral Modeling for Digital Predistortion of RF Power Amplifiers

In this paper, we propose a technique for comprehensive analysis of nonlinear and dynamic characteristics of multi-antenna transmitters (TXs). The analysis technique is enabled by the development of a Volterra series-based dual-input model for power amplifiers (PAs), which is capable of considering the joint effects of PA nonlinearity, antenna crosstalk, and mismatch for wideband modulated signals. By combining multiple instances of the PA model with linear dynamic antenna simulations, we develop the analysis technique. The proposed method allows the prediction of the output signal of every antenna in an arbitrarily sized TX array, as well as the total far-field radiated wave of the TX for any input signal with low computational effort. A 2.12-GHz four-element TX demonstrator based on GaAs PAs is implemented to verify simulation results with measurements. The proposed technique is a powerful tool to study hardware characteristics as, for example, the effects of antenna design and element spacing. It can be used in cases where experiments are not feasible, and thus aid the development of next generation wireless systems.

/pdf/prediction-of-nonlinear-distortion-in-wideband-active-1geord1jy6.pdf

Prediction of Nonlinear Distortion in Wideband Active Antenna Arrays

In this paper, we present a method to implement digital predistortion (DPD) memory models using lookup tables (LUTs) with linear interpolation and extrapolation. We introduce the required set of basis functions to describe this model. The DPD output is expressed as a linear combination of these basis functions and we show how to directly estimate the LUT entries using least squares. We show how this model achieves lower complexity at similar or better performance compared to polynomial models translated to LUTs with interpolation or models based on LUTs without interpolation whose coefficients are adapted directly. We refer to this model as the direct adaptation of LUTs with interpolation/extrapolation (DLUTI). In this paper we also introduce the composite memory polynomial model: a new polynomial model which is a hybrid between the generalized memory polynomial and the dynamic deviation reduction models. This model is used as a starting point to generate the final LUT-based model.

Digital Predistortion Using Lookup Tables With Linear Interpolation and Extrapolation: Direct Least Squares Coefficient Adaptation

Although the Cartesian signal decomposition has been the preferred representation in baseband polynomial power-amplifier (PA) behavioral models, this is not the only 2-D reference frame that could be considered for representing the input complex envelope signal. Indeed, in this paper, we demonstrate that, if the alternative polar representation is considered, the resulting Volterra series model is much more adequate to model the physical behavior of PA devices. This is the feature that supports the design of an innovative PA model, denominated the Polar Volterra model, which is more flexible and general than the traditional Volterra series commonly used in PA baseband modeling. The closeness of the new model formulation with the PA physical operation enabled, for the first time in PA low-pass equivalent behavioral modeling, the theoretical derivation of a Volterra series model directly from the PA circuit analysis. In fact, as the proposed model directly isolates such PA physical characteristics, a significant reduction of the number of model coefficients is achieved when compared with the traditional Cartesian Volterra model. Finally, validation results that highlight the advantages of the Polar Volterra model are presented. These were based on the laboratory measurements performed on two PAs with distinct architectures: a conventional class-AB amplifier and a polar transmitter.

Validation and Physical Interpretation of the Power-Amplifier Polar Volterra Model

This paper proves that the traditional way of deriving power amplifier low-pass equivalent complex-signal Volterra models from their original band-pass RF real-signal Volterra models is too restrictive, and so does not lead to an optimal model. Then, it proposes a much richer alternative approach. Instead of deriving the base-band Volterra model from the RF Volterra model, we started by a general Volterra series expansion of a complex-signal to only then impose the restrictions of odd parity required by the low-pass equivalent polynomial approximation. This way, not only we prove that the theoretical reticence that was raised to similar approaches previously proposed for the memoryless polynomial and the memory polynomial were unfounded, as experimental results fully justified this novel approach.

Base-band derived volterra series for power amplifier modeling

An efficient and accurate table-based behavioral model extraction for high-speed input/output (I/O) buffer behavior is presented in this paper The nonlinear current-voltage (I-V) and charge-voltage (Q-V) functions describing the graybox model structure are extracted via least-squares methods using identification signals recorded from large signal transient simulation The resulting continuous time-domain model is easily implemented as lookup table and leads to an increase in modeling accuracy, and a decrease in computation time, as is demonstrated in this paper Finally, its application in a realistic signal integrity scenario is presented, demonstrating a superior performance compared to that of the I/O buffer information specification model

Novel Extraction of a Table-Based I–Q Behavioral Model for High-Speed Digital Buffers/Drivers

This paper addresses the generation of behavioral models of digital integrated circuits (ICs) for signal and power integrity simulations. The proposed models are obtained by external measurements carried out at the device ports only and by the combined application of specialized state-of-the-art modeling techniques. The present approach exploits a behavioral formulation, leading to models reproducing all the behavior of the IC ports as the input/output buffers and the core power delivery network. The modeling procedure is demonstrated for a commercial nor Flash memory in 90-nm technology housed by a specifically designed test fixture.

Behavioral Modeling of IC Memories From Measured Data

The growing importance of signal integrity (SI) analysis in integrated circuits (ICs), revealed by modern system-in-package methods, is demanding for new models for the IC sub-systems which are both accurate, efficient and extractable by simple measurement procedures. This paper presents the contribution for the establishment of an integrated IC modeling approach whose performance is assessed by direct comparison with the signals measured in laboratory of two distinct memory IC devices. Based on the identification of the main blocks of a typical IC device, the modeling approach consists of a network of system-level sub-models, some of which with already demonstrated accuracy, which simulated the IC interfacing behavior. Emphasis is given to the procedures that were developed to validate by means of laboratory measurements (and not by comparison with circuit-level simulations) the model performance, which is a novel and important aspect that should be considered in the design of IC models that are useful for SI analysis.

/pdf/validation-by-measurements-of-an-ic-modeling-approach-for-5fx8x4dp56.pdf

Validation by Measurements of an IC Modeling Approach for SiP Applications

This paper presents a computational efficient table-based behavioral model implementation for transient simulation of high-speed digital I/O buffers. The proposed model is non-recursive and its formulation is supported by the analysis of the driver's physical constitution.

Hugo M. Teixeira

Papers

Base-band derived volterra series for power amplifier modeling

Novel Extraction of a Table-Based I–Q Behavioral Model for High-Speed Digital Buffers/Drivers

Behavioral Modeling of IC Memories From Measured Data

Validation by Measurements of an IC Modeling Approach for SiP Applications

Efficient table-based I-Q behavioral model for high-speed digital buffers/drivers