3-D Distributed Memory Polynomial Behavioral Model for Concurrent Dual-Band Envelope Tracking Power Amplifier Linearization

Gilabert, Pere L.; Montoro, Gabriel

doi:10.1109/tmtt.2014.2387825

Cited by 41 publications

(31 citation statements)

References 28 publications

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“…Unlike in macro base stations, where the DC power consumption in the transmitter chain is dominated by the PA, when targeting the linearization of small cells (or even handsets) the computational complexity and DC consumption of the digital signal processing and data conversion stages are critical. In addition, to linearize highly efficient amplification architectures based on dynamic supply or dynamic load modulation, the DPD behavioral model requires a huge number of parameters [5]. This can cause an ill-conditioned least squares (LS) estimation and at the same time increases the computational complexity of the overall DPD system.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Selection and Estimation of the Digital Predistorter Parameters for Power Amplifier Linearization

Pham

Montoro

López‐Bueno

et al. 2019

IEEE Trans. Microwave Theory Techn.

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This paper presents a new technique that dynamically estimates and updates the coefficients of a digital predistorter (DPD) for power amplifier (PA) linearization. The proposed technique is dynamic in the sense of estimating, at every iteration of the coefficient's update, only the minimum necessary parameters according to a criterion based on the residual estimation error. At the first step, the original basis functions defining the DPD in the forward path are orthonormalized for DPD adaptation in the feedback path by means of a precalculated principal components analysis (PCA) transformation. The robustness and reliability of the precalculated PCA transformation (i.e., PCA transformation matrix obtained off-line and only once) is tested and verified. Then, at the second step, a properly modified partial least squares (PLS) method, named dynamic partial least squares (DPLS), is applied to obtain the minimum and most relevant transformed components required for updating the coefficients of the DPD linearizer. The combination of the PCA transformation with the DPLS extraction of components is equivalent to a canonical correlation analysis (CCA) updating solution, which is optimum in the sense of generating components with maximum correlation (instead of maximum covariance as in the case of the DPLS extraction alone). The proposed dynamic extraction technique is evaluated and compared in terms of computational cost and performance with the commonly used QR decomposition approach for solving the least squares (LS) problem. Experimental results show that the proposed method (i.e., combining PCA with DPLS) drastically reduces the amount of DPD coefficients to be estimated while maintaining the same linearization performance.

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Section: Introductionmentioning

confidence: 99%

Dynamic Selection and Estimation of the Digital Predistorter Parameters for Power Amplifier Linearization

Pham

Montoro

López‐Bueno

et al. 2019

IEEE Trans. Microwave Theory Techn.

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“…However, unwanted distortion effects related to the slow envelope used to dynamically supply the PA as well as the inherent PA nonlinear behavior had to be compensated in order to comply with the required ACPR and NMSE levels. Therefore, the 3-D behavioral models for linearizing concurrent dual-band envelope tracking PAs were proposed [7]- [9].…”

Section: Introductionmentioning

confidence: 99%

Partial Least Squares Identification of Multi Look-Up Table Digital Predistorters for Concurrent Dual-Band Envelope Tracking Power Amplifiers

Pham

López‐Bueno

Wang

et al. 2018

IEEE Trans. Microwave Theory Techn.

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This paper presents a technique to estimate the coefficients of a multi look-up table (LUT) digital predistortion (DPD) architecture based on the partial least squares (PLS) regression method. The proposed 3-D distributed memory LUTs (3D-DML) architecture is suitable for efficient FPGA implementation and compensates for the distortion arising in concurrent dual-band envelope tracking (ET) power amplifiers (PAs). On the one hand, a new variant of the Orthogonal Matching Pursuit (OMP) algorithm is proposed to properly select only the best LUTs of the DPD function in the forward path and thus reducing the number of required coefficients. On the other hand, the PLS regression method is proposed to address both the regularization problem of the coefficient estimation and, at the same time, reducing the number of coefficients to be estimated in the DPD feedback identification path. Moreover, by exploiting the orthogonality of the PLS transformed matrix, the computational complexity of the parameters' identification can be significantly simplified. Experimental results will prove how it is possible to reduce the DPD complexity (i.e. the number of coefficients) in both forward and feedback paths while meeting the targeted linearity levels.

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“…Other 2D memory polynomial models have also been proposed [21][22][23] to reduce the number of model parameters by applying pruning techniques to the 2D-DPD model. In [24], a reduced complexity DB-DPD model is proposed for the envelope tracking concurrent dual-band PAs.…”

Section: Introductionmentioning

confidence: 99%

2D Extended envelope memory polynomial model for concurrent dual-band RF transmitters

Amin

Landin

Händel

et al. 2017

Int. J. Microw. Wireless Technol.

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The paper presents a two-dimensional (2D) extended envelope memory polynomial model for concurrent dual-band radio frequency (RF) power amplifiers (PAs). The model is derived based on the physical knowledge of a dual-band RF PA. The derived model contains cross-modulation terms not included in previously published models; these terms are found to be of importance for both behavioral modeling and digital predistortion (DPD). The performance of the derived model is evaluated both as the behavioral model and DPD, and the performance is compared with state-of-the-art 2D-DPD and dual-band generalized memory polynomial (DB-GMP) models. Experimental result shows that the proposed model resulted in normalized mean square error of 251.7/251.6 dB and adjacent channel error power ratio of 263.1/263.4 dB, for channel 1/2, whereas the 2D-DPD resulted in the largest model error and DB-GMP resulted in model parameters that are three times more than those resulted with the proposed model with the same performance. As pre-distorter, the proposed model resulted in adjacent channel power ratio of 255.8/254.6 dB for channel 1/2 and is 7-10 dB lower than those resulted with the 2D-DPD model and 2-4 dB lower compared with the DB-GMP model. I . I N T R O D U C T I O NGrowing demand for higher data rates along with the global concern on green technologies places challenging requirements on wireless transmitters. To accommodate higher data rates, significant efforts have been made to design multiband transmitters to support multiple standards in different frequency bands. More specifically, dual-band radiofrequency (RF) power amplifiers (PAs) that can accommodate signals in two different frequency bands have been successfully designed and tested [1][2][3].The non-linear behavior of RF PAs in the transmitter chain causes well-known hardware impairments. The non-linear distortion, which typically is dynamic, contains both in-band distortion and spectral regrowth, i.e. spectral spreading into the adjacent bands, thus interfering with signals in these channels. There are numerous publications on the linearization and efficiency improvement of single-input-singleoutput (SISO) RF PAs [4][5][6]. Digital predistortion (DPD) is a well-known technique and is applied to compensate PA nonlinear behavior and to improve the overall power efficiency of the RF transmitters. In DPD, an inverse mathematical model of the PA is used and put upstream of the PA to produce a linear output signal. Thus, an accurate mathematical model is required for the linearization of RF PAs.When dealing with the concurrent dual-band RF PAs, SISO DPD methods cannot be used, since there are two input and two output signals. In multi-band PAs, the nonlinear distortions are classified as in-band and cross-band distortions [7][8][9][10]. Both these distortion types should be included in behavioral models and DPD techniques for modeling and linearizing concurrent multi-band PAs.In recent years, several techniques have been proposed to compensate the non-linear distortions in con...

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3-D Distributed Memory Polynomial Behavioral Model for Concurrent Dual-Band Envelope Tracking Power Amplifier Linearization

Cited by 41 publications

References 28 publications

Dynamic Selection and Estimation of the Digital Predistorter Parameters for Power Amplifier Linearization

Dynamic Selection and Estimation of the Digital Predistorter Parameters for Power Amplifier Linearization

Partial Least Squares Identification of Multi Look-Up Table Digital Predistorters for Concurrent Dual-Band Envelope Tracking Power Amplifiers

2D Extended envelope memory polynomial model for concurrent dual-band RF transmitters

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