Digital predistortion of RF amplifiers using baseband injection for mobile broadband communications

Radio frequency (RF) power amplifiers (PAs) represent the most challenging design parts of wireless transmitters. In order to be more energy efficient, PAs should operate in nonlinear region where they produce distortion that significantly degrades the quality of signal at transmitter’s output. With the aim of reducing this distortion and improve signal quality, digital predistortion (DPD) techniques are widely used. This work focuses on improving the performances of DPDs in modern, next-generation wireless transmitters. A new adaptive DPD based on an iterative injection approach is developed and experimentally verified using a 4G signal. The signal performances at transmitter output are notably improved, while the proposed DPD does not require large digital signal processing memory resources and computational complexity. Moreover, the injection-based DPD theory is extended to be applicable in concurrent dual-band wireless transmitters. A cross-modulation problem specific to concurrent dual-band transmitters is investigated in detail and novel DPD based on simultaneous injection of intermodulation and cross-modulation distortion products is proposed. In order to mitigate distortion compensation limit phenomena and memory effects in highly nonlinear RF PAs, this DPD is further extended and complete generalised DPD system for concurrent dual-band transmitters is developed. It is clearly proved in experiments that the proposed predistorter remarkably improves the in-band and out-of-band performances of both signals. Furthermore, it does not depend on frequency separation between frequency bands and has significantly lower complexity in comparison with previously reported concurrent dual-band DPDs

Finding Structural Information of RF Power Amplifiers using an Orthogonal Non-Parametric Kernel Smoothing Estimator

A non-parametric technique for modeling the behavior of power amplifiers is presented. The proposed technique relies on the principles of density estimation using the kernel method and is suited for use in power amplifier modeling. The proposed methodology transforms the input domain into an orthogonal memory domain. In this domain, non-parametric static functions are discovered using the kernel estimator. These orthogonal, non-parametric functions can be fitted with any desired mathematical structure, thus facilitating its implementation. Furthermore, due to the orthogonality, the non-parametric functions can be analyzed and discarded individually, which simplifies pruning basis functions and provides a tradeoff between complexity and performance. The results show that the methodology can be employed to model power amplifiers, therein yielding error performance similar to state-of-the-art parametric models. Furthermore, a parameter-efficient model structure with 6 coefficients was derived for a Doherty power amplifier, therein significantly reducing the deployment's computational complexity. Finally, the methodology can also be well exploited in digital linearization techniques.Comment: Matlab sample code (15 MB): https://dl.dropboxusercontent.com/u/106958743/SampleMatlabKernel.zi

Dirty RF Signal Processing for Mitigation of Receiver Front-end Non-linearity

Moderne drahtlose Kommunikationssysteme stellen hohe und teilweise gegensätzliche Anforderungen an die Hardware der Funkmodule, wie z.B. niedriger Energieverbrauch, große Bandbreite und hohe Linearität. Die Gewährleistung einer ausreichenden Linearität ist, neben anderen analogen Parametern, eine Herausforderung im praktischen Design der Funkmodule. Der Fokus der Dissertation liegt auf breitbandigen HF-Frontends für Software-konfigurierbare Funkmodule, die seit einigen Jahren kommerziell verfügbar sind. Die praktischen Herausforderungen und Grenzen solcher flexiblen Funkmodule offenbaren sich vor allem im realen Experiment. Eines der Hauptprobleme ist die Sicherstellung einer ausreichenden analogen Performanz über einen weiten Frequenzbereich. Aus einer Vielzahl an analogen Störeffekten behandelt die Arbeit die Analyse und Minderung von Nichtlinearitäten in Empfängern mit direkt-umsetzender Architektur. Im Vordergrund stehen dabei Signalverarbeitungsstrategien zur Minderung nichtlinear verursachter Interferenz - ein Algorithmus, der besser unter "Dirty RF"-Techniken bekannt ist. Ein digitales Verfahren nach der Vorwärtskopplung wird durch intensive Simulationen, Messungen und Implementierung in realer Hardware verifiziert. Um die Lücken zwischen Theorie und praktischer Anwendbarkeit zu schließen und das Verfahren in reale Funkmodule zu integrieren, werden verschiedene Untersuchungen durchgeführt. Hierzu wird ein erweitertes Verhaltensmodell entwickelt, das die Struktur direkt-umsetzender Empfänger am besten nachbildet und damit alle Verzerrungen im HF- und Basisband erfasst. Darüber hinaus wird die Leistungsfähigkeit des Algorithmus unter realen Funkkanal-Bedingungen untersucht. Zusätzlich folgt die Vorstellung einer ressourceneffizienten Echtzeit-Implementierung des Verfahrens auf einem FPGA. Abschließend diskutiert die Arbeit verschiedene Anwendungsfelder, darunter spektrales Sensing, robuster GSM-Empfang und GSM-basiertes Passivradar. Es wird gezeigt, dass nichtlineare Verzerrungen erfolgreich in der digitalen Domäne gemindert werden können, wodurch die Bitfehlerrate gestörter modulierter Signale sinkt und der Anteil nichtlinear verursachter Interferenz minimiert wird. Schließlich kann durch das Verfahren die effektive Linearität des HF-Frontends stark erhöht werden. Damit wird der zuverlässige Betrieb eines einfachen Funkmoduls unter dem Einfluss der Empfängernichtlinearität möglich. Aufgrund des flexiblen Designs ist der Algorithmus für breitbandige Empfänger universal einsetzbar und ist nicht auf Software-konfigurierbare Funkmodule beschränkt.Today's wireless communication systems place high requirements on the radio's hardware that are largely mutually exclusive, such as low power consumption, wide bandwidth, and high linearity. Achieving a sufficient linearity, among other analogue characteristics, is a challenging issue in practical transceiver design. The focus of this thesis is on wideband receiver RF front-ends for software defined radio technology, which became commercially available in the recent years. Practical challenges and limitations are being revealed in real-world experiments with these radios. One of the main problems is to ensure a sufficient RF performance of the front-end over a wide bandwidth. The thesis covers the analysis and mitigation of receiver non-linearity of typical direct-conversion receiver architectures, among other RF impairments. The main focus is on DSP-based algorithms for mitigating non-linearly induced interference, an approach also known as "Dirty RF" signal processing techniques. The conceived digital feedforward mitigation algorithm is verified through extensive simulations, RF measurements, and implementation in real hardware. Various studies are carried out that bridge the gap between theory and practical applicability of this approach, especially with the aim of integrating that technique into real devices. To this end, an advanced baseband behavioural model is developed that matches to direct-conversion receiver architectures as close as possible, and thus considers all generated distortions at RF and baseband. In addition, the algorithm's performance is verified under challenging fading conditions. Moreover, the thesis presents a resource-efficient real-time implementation of the proposed solution on an FPGA. Finally, different use cases are covered in the thesis that includes spectrum monitoring or sensing, GSM downlink reception, and GSM-based passive radar. It is shown that non-linear distortions can be successfully mitigated at system level in the digital domain, thereby decreasing the bit error rate of distorted modulated signals and reducing the amount of non-linearly induced interference. Finally, the effective linearity of the front-end is increased substantially. Thus, the proper operation of a low-cost radio under presence of receiver non-linearity is possible. Due to the flexible design, the algorithm is generally applicable for wideband receivers and is not restricted to software defined radios

Digital electronic predistortion for optical communications

The distortion of optical signals has long been an issue limiting the performance of communication systems. With the increase of transmission speeds the effects of distortion are becoming more prominent. Because of this, the use of methods known from digital signal processing (DSP) are being introduced to compensate for them. Applying DSP to improve optical signals has been limited by a discrepancy in digital signal processing speeds and optical transmission speeds. However high speed Field Programmable Gate Arrays (FPGA) which are sufficiently fast have now become available making DSP experiments without costly ASIC implementation possible for optical transmission experiments. This thesis focuses on Look Up Table (LUT) based digital Electronic Predistortion (EPD) for optical transmission. Because it is only one out of many possible implementations of EPD, it has to be placed in context with other EPD techniques and other distortion combating techniques in general, especially since it is possible to combine the different techniques. Building an actual transmitter means that compromises and decisions have to be made in the design and implementation of an EPD based system. These are based on balancing the desire to achieve optimal performance with technological and economic limitations. This is partly done using optical simulations to asses the performance. This thesis describes a novel experimental transmitter that has been built as part of this research applying LUT based EPD to an optical signal. The experimental transmitter consists of a digital design (using a hardware description language) for a pair of FPGAs and an analogue optical/electronic setup including two standard DAC integrated circuits. The DSP in the transmitter compensated for both chromatic dispersion and self phase modulation. We achieved transmission of 10.7 Gb/s non-return-to-zero (NRZ) signals with a +4 dBm launch power over 450 km keeping the required optical-signal-to-noise-ratio (OSNR) for a bit-error-rate of 2x10^{-3} below 11 dB. In doing so we showed experimentally, for the first time, that nonlinear effects can be compensated with this approach and that the combination of FPGA-DAC is a viable approach for an experimental setup

Fiber link design considerations for cloud-Radio Access Networks

Analog radio over fiber (RoF) links may offer advantages for cloud-Radio Access Networks in terms of component cost, but the behavior of the distortion with large numbers of subcarriers needs to be understood. In this paper, this is presented in terms of the variation between subcarriers. Memory polynomial predistortion is also shown to compensate for RoF and wireless path distortion. Whether for digitized or analog links, it is shown that appropriate framing structure parameters must be used to assure performance, especially of time-division duplex systems

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

Experimental Demonstration and Performance Enhancement of 5G NR Multiband Radio over Fiber System Using Optimized Digital Predistortion

This paper presents an experimental realization of multiband 5G new radio (NR) optical front haul (OFH) based radio over fiber (RoF) system using digital predistortion (DPD). A novel magnitude-selective affine (MSA) based DPD method is proposed for the complexity reduction and performance enhancement of RoF link followed by its comparison with the canonical piece wise linearization (CPWL), decomposed vector rotation method (DVR) and generalized memory polynomial (GMP) methods. Similarly, a detailed study is shown followed by the implementation proposal of novel neural network (NN) for DPD followed by its comparison with MSA, CPWL, DVR and GMP methods. In the experimental testbed, 5G NR standard at 20 GHz with 50 MHz bandwidth and flexible-waveform signal at 3 GHz with 20 MHz bandwidth is used to cover enhanced mobile broad band and small cells scenarios. A dual drive Mach Zehnder Modulator having two distinct radio frequency signals modulates a 1310 nm optical carrier using distributed feedback laser for 22 km of standard single mode fiber. The experimental results are presented in terms of adjacent channel power ratio (ACPR), error vector magnitude (EVM), number of estimated coefficients and multiplications. The study aims to identify those novel methods such as MSA DPD are a good candidate to deploy in real time scenarios for DPD in comparison to NN based DPD which have a slightly better performance as compared to the proposed MSA method but has a higher complexity levels. Both, proposed methods, MSA and NN are meeting the 3GPP Release 17 requirements

A Ground-based L-band Radar System for Monitoring Forest Temporal Dynamics

L-band FMCW radar is implemented for monitoring forest dynamics. It took short-term and long-term measurements with an internal calibration system that guarantees stability and precision. The radar data is compared to in-situ measurement, which infers causal relationships between radar backscatter signal and forest physiology index such as tree dielectric. This paper explains the relationship between radar signals and environmental components such as precipitation based on the measurement. The radar demonstrates some interesting observations, for example, trees\u27 daily activity and freeze-thaw process