David Wisell

A comparative analysis of behavioral models for RF power amplifiers

A comparative study of nonlinear behavioral models with memory for radio-frequency power amplifier (PAs) is presented. The models are static polynomial, parallel Hammerstein (PH), Volterra, and radial basis-function neural network (RBFNN). Two PAs were investigated: one was designed for the third-generation (3G) mobile telecommunication systems and one was designed for the second-generation (2G). The RBFNN reduced the total model error slightly more than the PH, but the error out of band was significantly lower for the PH. The Volterra was found to give a lower model error than did a PH of the same nonlinear order and memory depth. The PH could give a lower model error than the best Volterra, since the former could be identified with a higher nonlinear order and memory depth. The qualitative conclusions are the same for the 2G and 3G PAs, but the model errors are smaller for the latter. For the 3G PA, a static polynomial gave a low model error as low as the best PH and lower than the RBFNN for the hardest cross validation. The models with memory, PH, and RBFNN, showed better cross-validation performance, in terms of lower model errors, than a static polynomial for the hardest cross validation of the 2G PA

Wide-band dynamic modeling of power amplifiers using radial-basis function neural networks

A radial-basis function neural network (RBFNN) has been used for modeling the dynamic nonlinear behavior of an RF power amplifier for third generation. In the model, the signals envelope is used. The model requires less training than a model using IQ data. Sampled input and output signals were used for identification and validation. Noise-like signals with bandwidths of 4 and 20 MHz were used. The RBFNN is compared to a parallel Hammerstein (PH) model. The two model types have similar performance when no memory is used. For the 4-MHz signal, the RBFNN has better in-band performance, whereas the PH is better out-of-band, when memory is used. For the 20-MHz signal, the models have similar performance in- and out-of-band. Used as a digital-predistortion algorithm, the best RBFNN with memory suppressed the lower (upper) adjacent channel power 7 dB (4 dB) compared to a memoryless nonlinear predistorter and 11 dB (13 dB) compared to the case of no predistortion for the same output power for a 4-MHz-wide signal.

A Technique to Extend the Bandwidth of an RF Power Amplifier Test Bed

In this paper, a method for increasing the bandwidth of a test bed for dynamic characterization of power amplifiers (PAs) is described. The technique is readily implemented using commercially available instruments, which makes it suitable for, e.g., production testing. The bandwidth extension technique is combined with coherent averaging of the measurements in order to simultaneously increase the bandwidth and dynamic range of the test bed. The errors in the obtained wideband signal are also estimated. The method is evaluated experimentally on a base station PA for the third-generation wideband code division multiple access system and on a Doherty amplifier. A tenfold increase in bandwidth to a total of 144 MHz and a more than 10-dB increase in dynamic range to 78 dB were obtained in practice. In addition, the obtained wideband signal is used for behavioral amplifier modeling.

A baseband time domain measurement system for dynamic characterization of power amplifiers with high dynamic range over large bandwidths

This paper describes, and discusses in some detail, a measurement system for dynamic characterization of power amplifiers. The system uses data that are generated and collected at baseband to accurately calculate AM/AM and AM/PM distortion as well as memory effects in the amplifiers. The limitations of the system in terms of dynamic range and bandwidth are discussed as well as techniques to overcome them. The system may serve as a tool both for designers of power amplifiers as well for development of amplifier models and systems for predistortion.

Characterization of Memory Effects in Power Amplifiers Using Digital Two-Tone Measurements

In this paper, a novel method to measure the amplitude and phase of two-tone third-order intermodulation products generated in a high-power amplifier is presented. The method is based on the sampled input and output signals of the amplifier. The presented measurement setup and the associated algorithms for the calculation of the amplitudes and phases are considerably faster and simpler than the current methods. By making use of the sampled input and output signals of the amplifier and the signal processing techniques, the need for a nonlinear reference, a tunable attenuator, and a phase shifter in the existing measurement setups is eliminated, which makes it simple and easy to use. Hence, this is a substantial simplification of the measurement setup compared to what has been reported earlier. The proposed measurement setup is also suitable for fast automated measurements, which is of interest for many applications that are both laboratory and production oriented. In addition, a method to increase the bandwidth of the measured signal is used to overcome the bandwidth limitation set by the Nyquist criteria for sampled systems. Measurements are done on two base-station high-power amplifiers and are found to be in agreement with theory and reference measurements.

Nonlinear behavioral modeling of power amplifiers using radial-basis function neural networks

A radial-basis function neural network (RBFNN) is proposed for modeling the dynamic nonlinear behavior of RF power amplifiers. In the model the signals envelope is used. The model requires less training than a model using both IQ-data. Sampled input and output signals from a power amplifier for 3G were used in the identification and validation. The RBFNN is compared with a parallel Hammerstein model. For a memory depth of one sample the RBFNN gives a better model, in- and out-of-band; for three samples the RBFNN reduces the in-band error more while the Hammerstein model reduces the error out-of-band more.

Extension of the hammerstein model for power amplifier applications

Due to the use of modem digital modulation methods power amplifiers are nowadays subjected to signals having a considerable bandwidth and a fast changing envelope. This means that traditional quasi-memoryless AMAM and AMPM characteristics are no longer enough to describe and model the behavior of power amplifiers [I]-[2], neither can they be successfully used for linearization. Instead, different models with memory have been introduced to accurately model power amplifiers over the bandwidth of interest [3]-[SI. In most cases the identification of the system parameters is done using multiple swept CW or two-tone measurements. An altemative approach is to extract the model parameters from sampled input output data as in [6]-[8]. The latter is the approach taken here.

Considerations when Designing and Using Virtual Instruments as Building Blocks in Flexible Measurement System Solutions

In this paper the software and hardware structure of a virtual instrument measurement system is discussed. The focus is on flexibility, modularity, generality and hardware independence. A software architecture that meets these requirements is proposed and discussed in some detail. The proposed software architecture has a layered structure that makes it suitable for implementation of versatile measurement systems. The measurement functionality is encapsulated in its own, hardware independent layer and communicates with its environment, e.g. physical hardware, through intermediary software components. Finally a measurement system for characterization of power amplifiers that is designed following the proposed software architecture, with software driven measurements, is implemented.

Three-Tone Characterization of Nonlinear Memory Effects in Radio-Frequency Power Amplifiers

A stepped three-tone measurement technique based on digitally modulated baseband signals is used in characterizing radio-frequency power amplifiers (PAs). The bandwidths of the stepped measurement were 8.8 MHz for the input signal and 26.4 MHz for the output signal. A PA designed for third-generation mobile telecommunication system was analyzed. The amplitude and phase of the third-order Volterra kernel were determined from the identified intermodulation products. The properties of the Volterra kernel along certain paths in the 3-D frequency space were analyzed and compared to some box models for nonlinear systems. The main symmetry of the third-order Volterra kernel of this PA was found to be of the type given by the cascaded quadratic nonlinearities with a linear filter in between (a Hammerstein-Wiener system), and frequency dependence, i.e., memory effects, was found to be due to the effects at the baseband.

Nonlinear Characterization of Multiple Carrier Power Amplifiers

In this paper the input signal dependence on the nonlinear transfer function of power amplifiers is discussed. It is shown by measurements that the nonlinear behavior of the amplifier does indeed depend on the input signal. This is seen to be true both for AM/AM and AM/PM distortion. The implication is that a traditionally VNA swept CW cannot be used to obtain the AM/AM and AM/PM distortion that will actually take place in the amplifier during real life conditions, and that test signals which closely resembles the signals that will actually be used are necessary. The focus is to present a new possible measurement methodology necessary to target the demands of accurate characterization raised by multiple carrier power amplifiers MCPA:s. We briefly discuss the mechanisms that lies behind this behavior. The test signal selection and creation is discussed, as well as a method of producing highly linear ¿80 dBc WCDMA signals for ACP testing. Finally we present practical measurement results on AM/AM and AM/PM distortion obtained with swept, pulsed and multi-tone input signals to prove the input signal dependence. Practical results is given for high power narrowband Class AB LDMOS amplifiers intended for the 2.11-2.17GHz WCDMA band and for medium power Class A GaAs FET amplifiers.