30 research outputs found

    Digital Signal Processing Techniques Applied to Radio over Fiber Systems

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    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

    Digital Predistorion of 5G Millimeter-Wave Active Phased Arrays using Artificial Neural Networks

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    Mixed-Signal Multimode Radio Software/Hardware Development Platform

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    Radio frequency power amplifiers (PAs) are the most challenging part of the design of radio systems since they dictate the overall system's performance in terms of power efficiency and distortion generation. The performance is further challenged by modern modulation schemes which are characterized by highly varying signal envelopes. In order to meet the spectrum mask requirements, PAs are usually operated at high power back-off to ensure linearity, at the cost of efficiency. To tackle this issue, many efficiency enhancement techniques have been presented in the literature. In fact, these techniques do increase the PA power efficiency at back-off, however, efficiency enhancement techniques do not ensure the linearity of the PA. Furthermore, these techniques may lead to additional distortion. On the other hand, several linearization techniques have been developed to mitigate the PA nonlinearity problem and allow the PA to operate at less back-off. Digital Pre-Distortion (DPD) technique is gaining more attention, as compared to other linearization techniques, thanks to its simple concept and advancements in digital signal processors (DSP) and signal converters. DPD technique consists of introducing a nonlinear function before the PA so that the overall cascaded system behaves linearly. It was clear from the literature that this technique showed good performance. Yet, it has primarily been validated using commercial test equipment, which has good capabilities, and far from the real world environment in which this technique would be implemented. Indeed, DPDs would need to be implemented in signal processors characterised by limited resources and computational accuracy. This thesis presents an implementation of several DPD models, namely look-up table (LUT), memoryless polynomial and memory polynomial (MP), on a field programmable gate array (FPGA). A novel model reformulation made this implementation possible in fixed-point arithmetic. Measurements were collected to validate the DPD models' implementation and an improvement of the signal quality was recorded in terms of error vector magnitude (EVM) and adjacent channel leakage ratio (ACLR). As many wireless access technologies must continue to coexist, multi-standard radio systems are required to reduce the cost while maintaining the interoperability. This thesis presents a development platform for multimode radio which comprises mixed-signal modules. The platform provides the capacity for hardware and software development. In fact, the FPGA under investigation allowed for the implementation of a baseband transceiver and DPD schemes. In addition, a software tool was developed as a dashboard to control and monitor the system. The radio system in the platform was optimized through the equalization of the feedback receiver frequency response performed through a simultaneous measurement of the amplitude ripple of the transmitter and receiver. Furthermore, a phase-coherent frequency synthesizer was designed to bring more flexibility by allowing the transmitter's carrier frequency to be different from the receiver's frequency

    Novel Predistortion System for 4G/5G Small-Cell and Wideband Transmitters

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    To meet the growing demand for mobile data, various technologies are being introduced to wireless networks to increase system capacity. On one hand, large number of small-cell base stations are adopted to serve the reduced cell size; on the other hand, millimeter wave (mm-wave) systems with large antenna arrays that transmit ultra-wideband signals are expected in fifth generation (5G) networks. Power amplifiers (PAs), responsible for boosting the radio frequency (RF) signal power, are the most critical components in base station transmitters, and dominate the overall efficiency and linearity of the system. The design challenges to balance the contradictory requirements of efficiency and linearity of the PAs are usually addressed by linearization techniques, particularly the digital predistortion (DPD) system. However, existing DPD solutions face increasing difficulties keeping up with new developments in base station technologies. When considering sub-6 GHz small-cell base station transmitters, analog and RF predistortion techniques have recently received renewed attention due to their inherent low power nature. Their achievable linearization capacity is significantly limited, however, largely by their implementation complexity in realizing the needed predistortion models in analog circuitry. On the other hand, despite significant developments in DPD models for wideband signals, the implementations of such DPD models in practical hardware have received relatively little attention. Yet the conventional implementation of a DPD engine is limited by the maximum clock frequency of the digital circuitry employed and cannot be scaled to satisfy the growing bandwidth of transmitted signals for 5G networks. Furthermore, both analog and digital solutions require a transmitter-observation-receiver (TOR) to capture the PA outputs, necessitates the use of analog-to-digital converters (ADCs) whose complexity and power consumption increase with signal bandwidth. Such trend is not scalable for future base stations, and new innovations in feedback and training methods are required. This thesis presents a number of contributions to address the above identified challenges. To reduce the power overhead of the linearization system, a digitally-assisted analog-RF predistortion (DA-ARFPD) system that uses a novel predistortion model is introduced. The proposed finite-impulse-response assisted envelope memory polynomial (FIR-EMP) model allows for a reduction of hardware implementation complexity while maintaining good linearization capacity and low power overhead. A two-step small-signal-assisted parameter identification (SSAPI) algorithm is devised to estimate the parameters of the two main blocks of the FIR-EMP model, such that the training can be completed efficiently. A DA-ARFPD test bench has been built, which incorporates major RF components, to assess the validity of the proposed FIR-EMP scheme and the SSAPI algorithm. Measurement results show that the proposed FIR-EMP model with SSAPI algorithm can successfully linearize multiple PAs driven with various wideband and carrier-aggregated signals of up to 80~MHz modulation bandwidths for sub-6 GHz systems. Next, a hardware-efficient real-time DPD system with scalable linearization bandwidth for ultra-wideband 5G mm-wave transmitters is proposed. It uses a novel parallel-processing DPD engine architecture to process multiple samples per clock cycle, overcomes the linearization bandwidth limit imposed by the maximum clock rate of digital circuits used in conventional DPD implementation. Potentially unlimited linearization bandwidth could be achieved by using the proposed system with current digital circuit technologies. The linearization performance and bandwidth scalability of the proposed system is demonstrated experimentally using a silicon-based Doherty (DPA) with 400 MHz wideband signal operating at 28 GHz, and over-the-air measurements using a 64-element beamforming array with 800 MHz wideband signal, also at 28 GHz. The proposed DPD system achieves over 2.4 GHz linearization bandwidth using only a 300 MHz core clock for the digital circuits. Finally, to reduce the power consumption and cost of the TOR, a new approach to train the predistorter using under-sampled feedback signal is presented. Using aliased samples of the PA's output captured at either baseband or intermedia frequency (IF), the proposed algorithm is able to compute the coefficients of the predistortion engine to linearize the PA using a direct learning architecture. Experimentally, both the baseband and IF schemes achieve linearization performance comparable to a full-rate system. Implemented together with a parallel-processing based DPD engine on a field-programmable gate array (FPGA) based system-on-chip (SOC), the proposed feedback and training solution achieves over 2.4~GHz linearization bandwidth using an ADC operating at a clock rate of 200 MHz. Its performance is demonstrated experimentally by linearizing a silicon DPA with 200 MHz and 400 MHz signals in conductive measurements, and a 64-element beamforming array with 400 MHz and 800 MHz signals in over-the-air testing

    Conversion analogique-numérique Sigma-Delta large bande appliquée à la mesure des non-linéarités des amplificateurs de puissance

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    Power amplifiers, which are essential elements of any communication system, will play a crucial role in the development of future communication systems. Today improving power amplifiers requires technological advances at the circuit device level, but one also must consider a more global approach. In particular, advances in digital processing can now correct in the early stage of the communication chain some distortions that are generated downstream in the chain. Digital pre-distortion is a correction technique for power amplifiers that has a growing interest because of its completely digital implementation and of its gains in linearity and energy consumption. This technique requires a feedback path where the analog-to-digital converter is a critical element. This component must satisfy the constraints of high resolution , wide bandwidth, and high linearity. In this thesis, we propose a new architecture of analog-to-digital converter based on bandpass Delta-Sigma modulators. This architecture takes advantage of operating bandpass modulators that are designed to work in parallel, each focusing on different frequencies, but also of a particular cascading arrangement to eliminate the useful signal, which has a high power, in order to reduce dynamics constraints. High-level design and simulations were carried out for discrete time and continuous time systems and also required the development of appropriate simulation tools.Les amplificateurs de puissance, éléments constitutifs essentiels de tout système de télécommunication, vont jouer un rôle capital dans le développement des futurs systèmes de communication. Aujourd'hui l'amélioration des amplificateurs de puissance nécessite un progrès technologique au niveau du composant lui même mais doit aussi tenir compte d'une approche plus globale. En particulier, le progrès dans les traitements numériques permet aujourd'hui de corriger en amont certaines distorsions qui seront générées en aval de la chaîne de communication. La pré-distorsion numérique est une technique de correction des amplificateurs de puissance qui connaît un intérêt grandissant de par son intégration complètement numérique et par les gains en linéarité et en consommation. Cette technique nécessite une voie de retour dont un élément critique est le convertisseur analogique-numérique. Ce composant doit répondre à des contraintes de résolution, de bande passante et de linéarité élevées. Dans cette thèse, nous proposons une nouvelle architecture de convertisseur analogique-numérique à base de modulateurs Sigma-Delta passe-bande. Cette architecture tire partie du fonctionnement passe bande des modulateurs que nous faisons travailler en parallèle, chacun centré sur différentes fréquences, mais aussi d'un agencement en cascade particulier pour éliminer le signal utile, qui est de forte puissance, dans le but de diminuer les contraintes de dynamique.La conception haut niveau et les simulations ont été menées pour des systèmes à temps discret et aussi à temps continu et a nécessité le développement d'outils adaptés de simulation se basant sur la boîte à outils Delta Sigma Toolbox de Richard Schreie

    A fast engineering approach to high efficiency power amplifier linearization for avionics applications

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    This PhD thesis provides a fast engineering approach to the design of digital predistortion (DPD) linearizers from several perspectives: i) enhancing the off-line training performance of open-loop DPD, ii) providing robustness and reducing the computational complexity of the parameters identification subsystem and, iii) importing machine learning techniques to favor the automatic tuning of power amplifiers (PAs) and DPD linearizers with several free-parameters to maximize power efficiency while meeting the linearity specifications. One of the essential parts of unmanned aerial vehicles (UAV) is the avionics, being the radio control one of the earliest avionics present in the UAV. Unlike the control signal, for transferring user data (such as images, video, etc.) real-time from the drone to the ground station, large transmission rates are required. The PA is a key element in the transmitter chain to guarantee the data transmission (video, photo, etc.) over a long range from the ground station. The more linear output power, the better the coverage or alternatively, with the same coverage, better SNR allows the use of high-order modulation schemes and thus higher transmission rates are achieved. In the context of UAV wireless communications, the power consumption, size and weight of the payload is of significant importance. Therefore, the PA design has to take into account the compromise among bandwidth, output power, linearity and power efficiency (very critical in battery-supplied devices). The PA can be designed to maximize its power efficiency or its linearity, but not both. Therefore, a way to deal with this inherent trade-off is to design high efficient amplification topologies and let the PA linearizers take care of the linearity requirements. Among the linearizers, DPD linearization is the preferred solution to both academia and industry, for its high flexibility and linearization performance. In order to save as many computational and power resources as possible, the implementation of an open-loop DPD results a very attractive solution for UAV applications. This thesis contributes to the PA linearization, especially on off-line training for open-loop DPD, by presenting two different methods for reducing the design and operating costs of an open-loop DPD, based on the analysis of the DPD function. The first method focuses on the input domain analysis, proposing mesh-selecting (MeS) methods to accurately select the proper samples for a computationally efficient DPD parameter estimation. Focusing in the MeS method with better performance, the memory I-Q MeS method is combined with feature extraction dimensionality reduction technique to allow a computational complexity reduction in the identification subsystem by a factor of 65, in comparison to using the classical QR-LS solver and consecutive samples selection. In addition, the memory I-Q MeS method has been proved to be of crucial interest when training artificial neural networks (ANN) for DPD purposes, by significantly reducing the ANN training time. The second method involves the use of machine learning techniques in the DPD design procedure to enlarge the capacity of the DPD algorithm when considering a high number of free parameters to tune. On the one hand, the adaLIPO global optimization algorithm is used to find the best parameter configuration of a generalized memory polynomial behavioral model for DPD. On the other hand, a methodology to conduct a global optimization search is proposed to find the optimum values of a set of key circuit and system level parameters, that properly combined with DPD linearization and crest factor reduction techniques, can exploit at best dual-input PAs in terms of maximizing power efficiency along wide bandwidths while being compliant with the linearity specifications. The advantages of these proposed techniques have been validated through experimental tests and the obtained results are analyzed and discussed along this thesis.Aquesta tesi doctoral proporciona unes pautes per al disseny de linealitzadors basats en predistorsió digital (DPD) des de diverses perspectives: i) millorar el rendiment del DPD en llaç obert, ii) proporcionar robustesa i reduir la complexitat computacional del subsistema d'identificació de paràmetres i, iii) incorporació de tècniques d'aprenentatge automàtic per afavorir l'auto-ajustament d'amplificadors de potència (PAs) i linealitzadors DPD amb diversos graus de llibertat per poder maximitzar l’eficiència energètica i al mateix temps acomplir amb les especificacions de linealitat. Una de les parts essencials dels vehicles aeris no tripulats (UAV) _es l’aviònica, sent el radiocontrol un dels primers sistemes presents als UAV. Per transferir dades d'usuari (com ara imatges, vídeo, etc.) en temps real des del dron a l’estació terrestre, es requereixen taxes de transmissió grans. El PA _es un element clau de la cadena del transmissor per poder garantir la transmissió de dades a grans distàncies de l’estació terrestre. A major potència de sortida, més cobertura o, alternativament, amb la mateixa cobertura, millor relació senyal-soroll (SNR) la qual cosa permet l’ús d'esquemes de modulació d'ordres superiors i, per tant, aconseguir velocitats de transmissió més altes. En el context de les comunicacions sense fils en UAVs, el consum de potència, la mida i el pes de la càrrega útil són de vital importància. Per tant, el disseny del PA ha de tenir en compte el compromís entre ample de banda, potència de sortida, linealitat i eficiència energètica (molt crític en dispositius alimentats amb bateries). El PA es pot dissenyar per maximitzar la seva eficiència energètica o la seva linealitat, però no totes dues. Per tant, per afrontar aquest compromís s'utilitzen topologies amplificadores d'alta eficiència i es deixa que el linealitzador s'encarregui de garantir els nivells necessaris de linealitat. Entre els linealitzadors, la linealització DPD és la solució preferida tant per al món acadèmic com per a la indústria, per la seva alta flexibilitat i rendiment. Per tal d'estalviar tant recursos computacionals com consum de potència, la implementació d'un DPD en lla_c obert resulta una solució molt atractiva per a les aplicacions UAV. Aquesta tesi contribueix a la linealització del PA, especialment a l'entrenament fora de línia de linealitzadors DPD en llaç obert, presentant dos mètodes diferents per reduir el cost computacional i augmentar la fiabilitat dels DPDs en llaç obert. El primer mètode se centra en l’anàlisi de l’estadística del senyal d'entrada, proposant mètodes de selecció de malla (MeS) per seleccionar les mostres més significatives per a una estimació computacionalment eficient dels paràmetres del DPD. El mètode proposat IQ MeS amb memòria es pot combinar amb tècniques de reducció del model del DPD i d'aquesta manera poder aconseguir una reducció de la complexitat computacional en el subsistema d’identificació per un factor de 65, en comparació amb l’ús de l'algoritme clàssic QR-LS i selecció de mostres d'entrenament consecutives. El segon mètode consisteix en l’ús de tècniques d'aprenentatge automàtic pel disseny del DPD quan es considera un gran nombre de graus de llibertat (paràmetres) per sintonitzar. D'una banda, l'algorisme d’optimització global adaLIPO s'utilitza per trobar la millor configuració de paràmetres d'un model polinomial amb memòria generalitzat per a DPD. D'altra banda, es proposa una estratègia per l’optimització global d'un conjunt de paràmetres clau per al disseny a nivell de circuit i sistema, que combinats amb linealització DPD i les tècniques de reducció del factor de cresta, poden maximitzar l’eficiència de PAs d'entrada dual de gran ample de banda, alhora que compleixen les especificacions de linealitat. Els avantatges d'aquestes tècniques proposades s'han validat mitjançant proves experimentals i els resultats obtinguts s'analitzen i es discuteixen al llarg d'aquesta tesi

    Improving linearity utilising adaptive predistortion for power amplifiers at mm-wave frequencies

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    The large unlicensed 3 GHz overlapping bandwidth that is available worldwide at 60 GHz has resulted in renewed interest in 60 GHz technology. This frequency band has made it attractive for short-range gigabit wireless communication. The power amplifier (PA) directly influences the performance and quality of this entire communication chain, as it is one of the final subsystems in the transmitter. Spectral efficient modulation schemes used at 60 GHz pose challenging requirements for the linearity of the PA. To improve the linearity, several external linearisation techniques currently exist, such as feedback, feedforward, envelope elimination and restoration, linear amplification with non-linear components and predistortion. This thesis is aimed at investigating and characterising the distortion components found in PAs at mm-wave frequencies and evaluating whether an adaptive predistortion (APD) linearisation technique is suitable to reduce these distortion components. After a thorough literature study and mathematical analysis, it was found that the third-order intermodulation distortion (IMD3) components were the most severe distortion components. Predistortion was identified as the most effective linearisation technique in terms of minimising these IMD3 components and was therefore proposed in this research. It does not introduce additional complexity and can easily be integrated with the PA. Furthermore, the approach is stable and has lower power consumption when compared to the aforementioned linearisation techniques. The proposed predistortion technique was developed compositely through this research by making it a function of the PA’s output power that was measured using a power detector. A comparator was used with the detected output power and the reference voltages to control the dynamic bias circuit of the variable gain amplifier. This provided control and flexibility on when to apply the predistortion to the PA and therefore allowing the linearity of the PA to be optimised. Three-stage non-linear and linear PAs were also designed at 60 GHz and implemented to compare the performance of the APD technique and form part of the hypothesis verification process. The 130 nm silicon-germanium (SiGe) bipolar and complementary metal oxide semiconductor (BiCMOS) technology from IBM was used for the simulation of the entire APD and PA design and for the fabrication of the prototype integrated circuits (ICs). This technology has the advantage of integrating the high performance, low power intensive SiGe heterojunction bipolar transistors (HBTs) with the CMOS technology. The SiGe HBTs have a high cut-off frequency (fT > 200 GHz), which is ideal for mm-wave PA applications and the CMOS components were integrated in the control logic of the digital circuitry. The simulations and IC layout were accomplished with Cadence Virtuoso. The implemented IC occupies an area of 1.8 mm by 2.0 mm. The non-linear PA achieves a Psat of 11.97 dBm and an IP1dB of -10 dBm. With the APD technique applied, the linearity of the PA is significantly improved with an IP1dB of -6 dBm and an optimum IMD3 reduction of 10 dB. Based on the findings and results of the applied APD technique, APD reduced intermodulation distortion (especially the IMD3) and is thus suitable to improve the linearity of PAs at mm-wave frequencies. To the knowledge of this author, no APD technique has been applied for PAs at 60 GHz, therefore the contribution of this research will assist future PA designers to characterise and optimise the reduction of the IMD3 components. This will result in improved linear output power from the PA and the use of complex modulation schemes at 60 GHz.Thesis (PhD)--University of Pretoria, 2014.Electrical, Electronic and Computer EngineeringPh
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