Dynamic selection and estimation of the digital predistorter parameters for power amplifier linearization

© © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.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 component 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.Peer ReviewedPostprint (author's final draft

Spectral weighting orthogonal matching pursuit algorithm for enhanced out-of-band digital predistortion linearization

"© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works."This paper presents a new variant of the orthogonal matching pursuit (OMP) algorithm for reducing the computational complexity of the digital predistortion (DPD) behavioral model in the forward path. The proposed spectral weighting OMP (SW-OMP) algorithm focuses on selecting the most relevant basis functions to compensate for the out-of-band residual distortion which may eventually be masked by the dominant in-band residual error. This basis selection is carried out in an off-line process that does not affect the computational complexity of the real-time closed-loop DPD but, on the contrary, reduces its complexity while enhancing the robustness. Experimental results show that by selecting the DPD coefficients with the SW-OMP, the inherent ACLR and NMSE degradation suffered when reducing the number of coefficients is mitigated under strong nonlinear operation, when compared to using the basis functions selected by the classical OMP algorithm.Peer ReviewedPostprint (author's final draft

Training data selection and dimensionality reduction for polynomial and artificial neural network MIMO adaptive digital predistortion

© 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes,creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.In 5G and beyond radios, the increased bandwidth, the fast-changing waveform scenarios, and the operation of large array multiple-input multiple-output (MIMO) transmitter architectures have challenged both the polynomial and the artificial neural network (ANN) MIMO adaptive digital predistortion (DPD) schemes. This article proposes training data selection methods and dimensionality reduction techniques that can be combined to enable relevant reductions of the DPD training time and the implementation complexity for MIMO transmitter architectures. In this work, the combination of an efficient uncorrelated equation selection (UES) mechanism together with orthogonal least squares (OLS) is proposed to reduce the training data length and the number of basis functions at every behavioral modeling matrix in the polynomial MIMO DPD scheme. For ANN MIMO DPD architectures, applying UES and principal component analysis (PCA) is proposed to reduce the input dataset length and features, respectively. The UES-OLS and the UES-PCA techniques are experimentally validated for a 2×2 MIMO test setup with strong power amplifier (PA) input and output crosstalk.This work was supported in part by the MCIN/AEI/10.13039/501100011033 under Project PID2020-113832RB-C22 and Project PID2020-113832RB-C21; and in part by the European Union-NextGenerationEU through the Spanish Recovery, Transformation and Resilience Plan, under Project TSI-063000-2021-121 (MINECO UNICO Programme).Peer ReviewedPostprint (author's final draft

Independent digital predistortion parameters estimation using adaptive principal component analysis

©2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.This paper presents an estimation/adaptation method based on the adaptive principal component analysis (APCA) technique to guarantee the identification of the minimum necessary parameters of a digital predistorter. The proposed estimation/adaptation technique is suitable for online field-programmable gate array or system on chip implementation. By exploiting the orthogonality of the resulting transformed matrix obtained with the APCA technique, it is possible to reduce the number of coefficients to be estimated which, at the same time, has a beneficial regularization effect by preventing ill-conditioning or overfitting problems. Therefore, this identification/adaptation method enhances the robustness of the parameter estimation and simplifies the adaptation by reducing the number of estimated coefficients. Due to the orthogonality of the new basis, these parameters can be estimated independently, thus allowing for scalability. Experimental results will show that it is possible to determine the minimum number of parameters to be estimated in order to meet the targeted linearity levels while ensuring a robust well-conditioned identification. Moreover, the results will show how thanks to the orthogonality property of the new basis functions, the coefficients of the digital predistorter can be estimated independently. This allows to tradeoff the digital predistorter adaptation time versus performance and hardware complexity.Peer ReviewedPostprint (author's final draft

Hydro-physical responses of gypseous and non-gypseous soils to livestock grazing in a semi-arid region of NE Spain

20 Pag., 4 Figs., 1 Tabl. The definitive version is available at: http://www.sciencedirect.com/science/journal/03783774Pasture productivity depends on soil hydro-physical properties, which in turn are deeply affected by livestock grazing. However, the comparative response of different soil types, and particularly gypseous soil types, to grazing has hardly been studied before. This paper compares the effect of grazing on the soil hydro-physical properties of silty gypseous (Gy) and non-gypseous (NGy) soils located in a semi-arid region (Middle Ebro Valley, NE, Spain). Two different soil managements were selected: ungrazed natural shrubland (N) and grazed shrubland (GR) soils. The gypsum, CaCO3 and organic matter content (OM), soil texture, soil bulk density ( b), penetration resistance (PR), saturated sorptivity (S), hydraulic conductivity (K), and the water retention curve (WRC) for undisturbed soil samples from 1 to 10 cm depth soil layer were measured. The b and PR in NGy soils were significantly higher than those observed in the Gy ones. Soil compaction due to grazing treatment tended to increase b and decrease the K and S values. While no differences in PR were observed in the Gy soils between grazing treatments, the PR measured in the NGy soils under GR was significantly higher than the corresponding values observed under N. Differences in K and S between GR and N treatments were only significant (p < 0.05) in NGy soils, where K and S values under the N treatment were almost four times greater than the corresponding values measured under GR. Overall, no differences in the WRCs were observed between soil types and grazing treatments. While the WRCs of NGy soils were not significantly affected by the grazing treatment, Gy soils under N treatment present a significantly higher level of soil macropores than under GR treatment. The hydro-physical features of Gy soils tended to be less affected by grazing than those of the NGy soils. These results suggest that livestock grazing, in both Gy and NGy soils, has a negative effect on the physical soil properties, which should be taken into account by land managers of these semi-arid regions where silty gypseous and non-gypseous areas coexist.This research was supported by Aragón regional government and La Caixa (Grants: GA-LC020/2010; GA-LC-010/2008) and the CSIC (Grant: PIE-200930I145).Peer reviewe

Design, implementation and testing of a real-time mobile WiMAX testbed featuring MIMO technology

Postprint (author’s final draft

A real-time FPGA-based implementation of a high-performance MIMO-OFDM mobile WiMAX transmitter

The Multiple Input Multiple Output (MIMO)-Orthogonal Frequency Division Multiplexing (OFDM) is considered a key technology in modern wireless-access communication systems. The IEEE 802.16e standard, also denoted as mobile WiMAX, utilizes the MIMO-OFDM technology and it was one of the first initiatives towards the roadmap of fourth generation systems. This paper presents the PHY-layer design, implementation and validation of a high-performance real-time 2x2 MIMO mobile WiMAX transmitter that accounts for low-level deployment issues and signal impairments. The focus is mainly laid on the impact of the selected high bandwidth, which scales the implementation complexity of the baseband signal processing algorithms. The latter also requires an advanced pipelined memory architecture to timely address the datapath operations that involve high memory utilization. We present in this paper a first evaluation of the extracted results that demonstrate the performance of the system using a 2x2 MIMO channel emulation.Postprint (published version

MATLAB as a Design and Verification Tool for the Hardware Prototyping of Wireless Communication Systems

Peer ReviewedPostprint (published version

Nonuniversal large-size asymptotics of the Lyapunov exponent in turbulent globally coupled maps

Globally coupled maps (GCMs) are prototypical examples of high-dimensional dynamical systems. Interestingly, GCMs formed by an ensemble of weakly coupled identical chaotic units generically exhibit a hyperchaotic “turbulent” state. A decade ago, Takeuchi et al. [Phys. Rev. Lett. 107, 124101 (2011)] theorized that in turbulent GCMs the largest Lyapunov exponent (LE), λ(N), depends logarithmically on the system size N: λ∞−λ(N)≃c/lnN. We revisit the problem and analyze, by means of analytical and numerical techniques, turbulent GCMs with positive multipliers to show that there is a remarkable lack of universality, in conflict with the previous prediction. In fact, we find a power-law scaling λ∞−λ(N)≃c/Nγ, where γ is a parameter-dependent exponent in the range 0<γ≤1. However, for strongly dissimilar multipliers, the LE varies with N in a slower fashion, which is here numerically explored. Although our analysis is only valid for GCMs with positive multipliers, it suggests that a universal convergence law for the LE cannot be taken for granted in general GCMs.D.V. acknowledges support by Agencia Estatal de Investigación (Spain), and European Social Fund (EU) under Grant No. BES-2017-081808 of the FPI Programme. We acknowledge support by Agencia Estatal de Investigación (Spain), and European Regional Development Fund (EU) under Project No. FIS2016-74957-P (AEI/FEDER, EU)

Multi-dimensional LUT-based digital predistorter for concurrent dual-band envelope tracking power amplifier linearization

©2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.This paper presents a multi lookup table (LUT) implementation scheme for the 3D distributed memory polynomial (3D-DMP) behavioral model used in Digital Predistortion (DPD) linearization for concurrent dual-band envelope tracking (ET) power amplifiers (PAs). The proposed 3DDistributed Memory LUTs (3D-DML) architecture is suitable for efficient FPGA implementation. In order to optimize the linearization performance as well as to reduce the number of resources of the 3D-DML model, a new variant of the Orthogonal Matching Pursuit (OMP) algorithm is proposed to properly select the best LUTs. Experimental results show that the proposed strategy reduces the number of LUTs (i.e. the number of coefficients) while meeting the targeted linearity levels.Peer ReviewedPostprint (author's final draft