Contribution to dimensionality reduction of digital predistorter behavioral models for RF power amplifier linearization

The power efficiency and linearity of radio frequency (RF) power amplifiers (PAs) are critical in wireless communication systems. The main scope of PA designers is to build the RF PAs capable to maintain high efficiency and linearity figures simultaneously. However, these figures are inherently conflicted to each other and system-level solutions based on linearization techniques are required. Digital predistortion (DPD) linearization has become the most widely used solution to mitigate the efficiency versus linearity trade-off. The dimensionality of the DPD model depends on the complexity of the system. It increases significantly in high efficient amplification architectures when considering current wideband and spectrally efficient technologies. Overparametrization may lead to an ill-conditioned least squares (LS) estimation of the DPD coefficients, which is usually solved by employing regularization techniques. However, in order to both reduce the computational complexity and avoid ill-conditioning problems derived from overparametrization, several efforts have been dedicated to investigate dimensionality reduction techniques to reduce the order of the DPD model. This dissertation contributes to the dimensionality reduction of DPD linearizers for RF PAs with emphasis on the identification and adaptation subsystem. In particular, several dynamic model order reduction approaches based on feature extraction techniques are proposed. Thus, the minimum number of relevant DPD coefficients are dynamically selected and estimated in the DPD adaptation subsystem. The number of DPD coefficients is reduced, ensuring a well-conditioned LS estimation while demanding minimum hardware resources. The presented dynamic linearization approaches are evaluated and compared through experimental validation with an envelope tracking PA and a class-J PA The experimental results show similar linearization performance than the conventional LS solution but at lower computational cost.La eficiencia energetica y la linealidad de los amplificadores de potencia (PA) de radiofrecuencia (RF) son fundamentales en los sistemas de comunicacion inalambrica. El principal objetivo a alcanzar en el diserio de amplificadores de radiofrecuencia es lograr simultaneamente elevadas cifras de eficiencia y de linealidad. Sin embargo, estas cifras estan inherentemente en conflicto entre si, y se requieren soluciones a nivel de sistema basadas en tecnicas de linealizacion. La linealizacion mediante predistorsion digital (DPD) se ha convertido en la solucion mas utilizada para mitigar el compromise entre eficiencia y linealidad. La dimension del modelo del predistorsionador DPD depende de la complejidad del sistema, y aumenta significativamente en las arquitecturas de amplificacion de alta eficiencia cuando se consideran los actuales anchos de banda y las tecnologfas espectralmente eficientes. El exceso de parametrizacion puede conducir a una estimacion de los coeficientes DPD, mediante minimos cuadrados (LS), mal condicionada, lo cual generalmente se resuelve empleando tecnicas de regularizacion. Sin embargo, con el fin de reducir la complejidad computacional y evitar dichos problemas de mal acondicionamiento derivados de la sobreparametrizacion, se han dedicado varies esfuerzos para investigar tecnicas de reduccion de dimensionalidad que permitan reducir el orden del modelo del DPD. Esta tesis doctoral contribuye a aportar soluciones para la reduccion de la dimension de los linealizadores DPD para RF PA, centrandose en el subsistema de identificacion y adaptacion. En concrete, se proponen varies enfoques de reduccion de orden del modelo dinamico, basados en tecnicas de extraccion de caracteristicas. El numero minimo de coeficientes DPD relevantes se seleccionan y estiman dinamicamente en el subsistema de adaptacion del DPD, y de este modo la cantidad de coeficientes DPD se reduce, lo cual ademas garantiza una estimacion de LS bien condicionada al tiempo que exige menos recursos de hardware. Las propuestas de linealizacion dinamica presentados en esta tesis se evaluan y comparan mediante validacion experimental con un PA de seguimiento de envolvente y un PA tipo clase J. Los resultados experimentales muestran unos resultados de linealizacion de los PA similares a los obtenidos cuando se em plea la solucion LS convencional, pero con un coste computacional mas reducido.Postprint (published version

Digital Signal Processing Techniques Applied to Radio over Fiber Systems

The dissertation aims to analyze different Radio over Fiber systems for the front-haul applications. Particularly, analog radio over fiber (A-RoF) are simplest and suffer from nonlinearities, therefore, mitigating such nonlinearities through digital predistortion are studied. In particular for the long haul A-RoF links, direct digital predistortion technique (DPDT) is proposed which can be applied to reduce the impairments of A-RoF systems due to the combined effects of frequency chirp of the laser source and chromatic dispersion of the optical channel. Then, indirect learning architecture (ILA) based structures namely memory polynomial (MP), generalized memory polynomial (GMP) and decomposed vector rotation (DVR) models are employed to perform adaptive digital predistortion with low complexities. Distributed feedback (DFB) laser and vertical capacity surface emitting lasers (VCSELs) in combination with single mode/multi-mode fibers have been linearized with different quadrature amplitude modulation (QAM) formats for single and multichannel cases. Finally, a feedback adaptive DPD compensation is proposed. Then, there is still a possibility to exploit the other realizations of RoF namely digital radio over fiber (D-RoF) system where signal is digitized and transmits the digitized bit streams via digital optical communication links. The proposed solution is robust and immune to nonlinearities up-to 70 km of link length. Lastly, in light of disadvantages coming from A-RoF and D-RoF, it is still possible to take only the advantages from both methods and implement a more recent form knows as Sigma Delta Radio over Fiber (S-DRoF) system. Second Order Sigma Delta Modulator and Multi-stAge-noise-SHaping (MASH) based Sigma Delta Modulator are proposed. The workbench has been evaluated for 20 MHz LTE signal with 256 QAM modulation. Finally, The 6x2 GSa/s sigma delta modulators are realized on FPGA to show a real time demonstration of S-DRoF system. The demonstration shows that S-DRoF is a competitive competitor for 5G sub-6GHz band applications

CMOS design of chaotic oscillators using state variables: a monolithic Chua's circuit

This paper presents design considerations for monolithic implementation of piecewise-linear (PWL) dynamic systems in CMOS technology. Starting from a review of available CMOS circuit primitives and their respective merits and drawbacks, the paper proposes a synthesis approach for PWL dynamic systems, based on state-variable methods, and identifies the associated analog operators. The GmC approach, combining quasi-linear VCCS's, PWL VCCS's, and capacitors is then explored regarding the implementation of these operators. CMOS basic building blocks for the realization of the quasi-linear VCCS's and PWL VCCS's are presented and applied to design a Chua's circuit IC. The influence of GmC parasitics on the performance of dynamic PWL systems is illustrated through this example. Measured chaotic attractors from a Chua's circuit prototype are given. The prototype has been fabricated in a 2.4- mu m double-poly n-well CMOS technology, and occupies 0.35 mm/sup 2/, with a power consumption of 1.6 mW for a +or-2.5-V symmetric supply. Measurements show bifurcation toward a double-scroll Chua's attractor by changing a bias current

Modelação comportamental e pré-distorção digital de transmissores de rádio-frequência

Doutoramento em Engenharia ElectrotécnicaNos atuais sistemas de telecomunicações, os transmissores de rádio-frequência são desenvolvidos tendo maioritariamente em conta a eficiência da conversão da potência fornecida da fonte em potência de rádio-frequência. Este tipo de desenho resulta em amplificadores de potência com características de transmissão não-lineares, que distorcem severamente o envelope de informação no processo de amplificação, gerando distorção fora da banda. Para corrigir este problema utiliza-se um processo de compensação não linear, sendo que a pré-distorção digital se tem favorecido pela sua flexibilidade e precisão. Este método é tipicamente aplicado de uma forma cega, por força bruta até se obter a compensação desejada. No entanto, quando o método se mostra ineficaz, como se verificou em amplificadores de potência baseados em transístores de nitreto de gálio, é difícil saber o que modificar nos sistemas para os tornar de novo úteis. De forma a compreender e desenhar sistemas de pré-distorção digital robustos é necessário, por um lado, perceber o comportamento dos amplificadores de rádio-frequência, por outro, perceber as limitações e relações entre os modelos digitais e o comportamento real do amplificador. Nesse sentido, esta tese explora e descreve estas relações de forma a suportar a escolha de modelos de pré-distorção, desenvolve novos modelos baseados no comportamento dos transístores, e propõe métodos de caracterização para os amplificadores de RF.In current telecommunication systems, the main concern when developing the radio frequency transmitter is power efficiency. This type of design generally leads to a highly nonlinear transmission characteristic, mainly due to the radio frequency power amplifier. This nonlinear transmission severely distorts the information envelope, leading to spectral regrowth, out-of-band distortion. To correct this problem a nonlinear compensation process is employed. For this application, digital predistortion is generally favored for its flexibility and accuracy. Digital predistortion is mostly applied in a blind manner, using brute force until the desired compensation is achieved. Because of this, when the method fails, as it has in gallium nitride based power amplifiers, it is difficult to modify the system to achieve the desired results. To understand and design robust predistortion systems, it is both necessary to have knowledge of the power amplifiers’ behavior, on one hand, and understand the limitations and relations between the digital models and these behaviors, on the other. To do this, this thesis explores and describes these relationships, granting support to the digital predistortion model choice, it further develops new predistortion models based on the physics of the transistors’ behaviors, and it proposes methods for the characterization of radio frequency power amplifiers

Behavioral modeling techniques for power amplifier digital pre-distortion

Abstract. The dramatic increase in the capacity of telecommunication networks has increased the requirements of the devices, one example of which is the continuously widening bandwidth. Using broadband signals requires often high linearity from the transmitter — and especially from the power amplifier at the end of the transmitter chain — but at the same time, it should operate as efficiently as possible. The power amplifier is the most power consuming component in the transmitter and inherently nonlinear, so its linearization is an essential part of the overall system performance. Of the current linearization techniques, digital pre-distortion has established itself as the most common tool for providing better linearity and efficiency in a power amplifier and transmitter. In this thesis, the performance of power amplifier models used in digital pre-distortion was investigated and their differences compared to the more complex reference model used in the actual base station product. The aim of this thesis was to create a behavioral model that corresponds the physical component as accurately as the reference model. This behavioral model could be used for example to design and optimize a power amplifier and linearization algorithm without the need for the secret model for the product. This, in its turn, would result in more efficient work with third parties such as component vendors and reduce the linearization time. The performance parameters of the behavioral models were introduced at the beginning of the thesis. These were also used in later parts to analyse the measurement results. Power amplifier linearization measurements were performed under laboratory conditions on a MATLAB® test bench. From the results, it was found that the use of a simple memoryless behavioral model is not enough to describe the physical nonlinear component with sufficient accuracy. The results also showed that the complexity of the model reduces its accuracy if the model coefficients are not correctly positioned. In this thesis, we succeeded in creating a memory model that describes the reference model sufficiently accurately on several meters, taking into account also the memory effects of the power amplifier. This thesis thus provides a good basis for further development of the actual modeling tool for product projects.Tehovahvistimen käyttäytymistason mallinnustekniikat esisärötyksen tueksi. Tiivistelmä. Tietoliikenneverkkojen kapasiteetin räjähdysmäinen kasvu on lisännyt laitteiden vaatimuksia, joista yhtenä esimerkkinä on jatkuvasti suureneva kaistanleveys. Laajakaistaiset signaalit vaativat usein lähettimeltä — ja etenkin lähettimen loppupäässä olevalta tehovahvistimelta — korkeaa lineaarisuutta, mutta samalla sen on toimittava mahdollisimman tehokkaasti. Tehovahvistin on lähettimen eniten tehoa kuluttava komponentti ja luonnostaan epälineaarinen, joten sen linearisointi on oleellinen osa koko systeemin suorituskykyä. Nykyisistä linearisointitekniikoista digitaalinen esisärötys on vakiinnuttanut paikkansa yleisimpänä työkaluna paremman lineaarisuuden ja tehokkuuden saavuttamiseksi tehovahvistimessa. Tässä diplomityössä tutkittiin digitaalisessa esisärötyksessä käytettävien käyttäytymistason tehovahvistinmallien suorituskykyjä ja niiden eroja varsinaisessa tukiasematuotteessa käytettävään, monimutkaisempaan referenssimalliin verrattuna. Työn tavoitteena oli luoda käyttäytymismalli, jolla voidaan kuvata fyysistä komponenttia yhtä tarkasti kuin referenssimallilla. Mallia voitaisiin käyttää esimerkiksi uuden tehovahvistimen suunnittelussa ilman, että kaupalliseen tuotteeseen tulevaa, salaista referenssimallia on tarve käyttää. Näin voitaisiin tehostaa työskentelyä ulkopuolisten tahojen, kuten komponenttitoimittajien kanssa ja vähentää linearisointiin käytettävää aikaa. Työn alussa esiteltiin käyttäytymismallien suorituskykyparametrit, joita käytettiin mittaustulosten analysointiin. Tehovahvistimien linearisointimittaukset suoritettiin laboratorio-olosuhteissa MATLAB®-testipenkissä. Mittauksissa todettiin, että yksinkertainen, muistiton käyttäytymismalli ei riitä kuvaamaan fyysistä komponenttia riittävän tarkasti. Tuloksista pääteltiin myös, että liian kompleksinen malli heikentää sen tarkkuutta. Työssä onnistuttiin luomaan muistillinen käyttäytymismalli, joka kuvaa referenssimallia riittävän tarkasti usealla eri mittarilla tarkastellen — huomioiden osaltaan myös tehovahvistimen muistiefektejä. Tämä opinnäytetyö tarjoaa siis hyvän pohjan varsinaisen mallinnustyökalun jatkokehitykselle tuoteprojekteihin

An implementation of the redirected learning architecture for digital pre-distortion

Digital pre-distortion is a digital signal processing technique that\u27s used to linearize the output of various systems. A common application of digital pre-distortion is to linearize microwave power amplifier circuits, because non-linear distortion can lead to inefficient performance and out of band emissions. Since its conception, several different architectures have been developed for digital pre-distortion. There are online architectures, such as the indirect learning architecture, where signal processing is done while the amplifier is running. There are also offline architectures, such as the direct learning architecture and the relatively new redirected learning architecture, where the signal processing is done using previous input and output data from the amplifier to create a pre-distorted signal. The choice of which architecture to use often comes down to a trade off between performance and complexity. However, a common problem exists between these architectures; the complexity of the pre-distortion technique is bound to the complexity of the system\u27s architecture. Most digital pre-distortion systems in use today use Volterra series filters and their derivatives for behavioral modeling or simple look-up tables. The complexity of applying a given behavioral model to an input signal varies little between architectures, so for a given model the question becomes which architecture will yield the greatest performance. Online methods have excellent performance, though the system required to train the models is computationally complex, as the algorithms to implement them require many calculations in a short period of time; whereas offline methods do not require an expensive training system but may not perform as well. For this reason, it is often desirable to use offline methods to save on system costs and engineering time. Most offline digital pre-distortion systems use the direct learning architecture, however newer architectures may be able to outperform the direct learning architecture with a given behavioral model.In this thesis it is shown how the redirected learning architecture was used to mitigate harmonic distortion by about 30~dB more than the indirect learning architecture. The direct, indirect, and redirected learning architectures are presented, as well as various behavioral models. This is followed by an analysis of the redirected learning architecture. Finally an implementation of the redirected learning model is presented using ADS-Matlab co-simulation. The results are then discussed to show the potential of the redirected learning method