Comparative Analysis of Greedy Pursuits for the Order Reduction of Wideband Digital Predistorters

This paper provides a review of greedy pursuits for optimizing Volterra-based behavioral models structure and estimating its parameters. An experimental comparison of the digital predistortion (DPD) linearization performance achieved by these approaches for model-order reduction, such as compressive sampling matching pursuit (CoSaMP), subspace pursuit (SP), orthogonal matching pursuit (OMP), and the novel doubly OMP (DOMP), is presented. A benchmark of the techniques in the DPD of a commercial class AB power amplifier (PA) and a class J PA operating over a 15-MHz Long-Term Evolution (LTE) signal is presented, giving a clear overview of their pruning characteristics in terms of linearization indicators and regressor selection capabilities. In addition, the benchmark is run in a cross-validation scheme by identifying the DPD with a 30-MHz 5G-new radio (NR) signal and validating with the same signal and a 20-MHz multicarrier wideband code division multiple access (WCDMA) signal. The DOMP is shown to be a promising technique since it achieves an enhanced model-order reduction for a similar linearization performance and precision

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

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

Compact Digital Predistortion for Multi-band and Wide-band RF Transmitters

This thesis is focusing on developing a compact digital predistortion (DPD) system which costs less DPD added power consumptions. It explores a new theory and techniques to relieve the requirement of the number of training samples and the sampling-rate of feedback ADCs in DPD systems. A new theory about the information carried by training samples is introduced. It connects the generalized error of the DPD estimation algorithm with the statistical properties of modulated signals. Secondly, based on the proposed theory, this work introduces a compressed sample selection method to reduce the number of training samples by only selecting the minimal samples which satisfy the foreknown probability information. The number of training samples and complex multiplication operations required for coefficients estimation can be reduced by more than ten times without additional calculation resource. Thirdly, based on the proposed theory, this thesis proves that theoretically a DPD system using memory polynomial based behavioural modes and least-square (LS) based algorithms can be performed with any sampling-rate of feedback samples. The principle, implementation and practical concerns of the undersampling DPD which uses lower sampling-rate ADC are then introduced. Finally, the observation bandwidth of DPD systems can be extended by the proposed multi-rate track-and-hold circuits with the associated algorithm. By addressing several parameters of ADC and corresponding DPD algorithm, multi-GHz observation bandwidth using only a 61.44MHz ADC is achieved, and demonstrated the satisfactory linearization performance of multi-band and continued wideband RF transmitter applications via extensive experimental tests

Digital Pre-distortion for Interference Reduction in Dynamic Spectrum Access Networks

Given the ever increasing reliance of today’s society on ubiquitous wireless access, the paradigm of dynamic spectrum access (DSA) as been proposed and implemented for utilizing the limited wireless spectrum more efficiently. Orthogonal frequency division multiplexing (OFDM) is growing in popularity for adoption into wireless services employing DSA frame- work, due to its high bandwidth efficiency and resiliency to multipath fading. While these advantages have been proven for many wireless applications, including LTE-Advanced and numerous IEEE wireless standards, one potential drawback of OFDM or its non-contiguous variant, NC-OFDM, is that it exhibits high peak-to-average power ratios (PAPR), which can induce in-band and out-of-band (OOB) distortions when the peaks of the waveform enter the compression region of the transmitter power amplifier (PA). Such OOB emissions can interfere with existing neighboring transmissions, and thereby severely deteriorate the reliability of the DSA network. A performance-enhancing digital pre-distortion (DPD) technique compensating for PA and in-phase/quadrature (I/Q) modulator distortions is proposed in this dissertation. Al- though substantial research efforts into designing DPD schemes have already been presented in the open literature, there still exists numerous opportunities to further improve upon the performance of OOB suppression for NC-OFDM transmission in the presence of RF front-end impairments. A set of orthogonal polynomial basis functions is proposed in this dissertation together with a simplified joint DPD structure. A performance analysis is presented to show that the OOB emissions is reduced to approximately 50 dBc with proposed algorithms employed during NC-OFDM transmission. Furthermore, a novel and intuitive DPD solution that can minimize the power regrowth at any pre-specified frequency in the spurious domain is proposed in this dissertation. Conventional DPD methods have been proven to be able to effectively reduce the OOB emissions that fall on top of adjacent channels. However more spectral emissions in more distant frequency ranges are generated by employing such DPD solutions, which are potentially in violation of the spurious emission limit. At the same time, the emissions in adjacent channel must be kept under the OOB limit. To the best of the author’s knowledge, there has not been extensive research conducted on this topic. Mathematical derivation procedures of the proposed algorithm are provided for both memoryless nonlinear model and memory-based nonlinear model. Simulation results show that the proposed method is able to provide a good balance of OOB emissions and emissions in the far out spurious domain, by reducing the spurious emissions by 4-5 dB while maintaining the adjacent channel leakage ratio (ACLR) improvement by at least 10 dB, comparing to the PA output spectrum without any DPD

On the Optimum Number of Coefficients of Sparse Digital Predistorters: A Bayesian Approach

This work presents insights on the application of the Bayesian information criterion (BIC) to fix the optimum number of coefficients in the Volterra series applied to the modeling and linearization of power amplifiers (PAs). The BIC is transformed from a rule to be applied after selection techniques to a stopping criterion, which enables the halting of the algorithm when a condition is reached. This study reveals that the BIC is equivalent to allow a certain identification normalized mean square error (NMSE) decrease after the inclusion of a model component. Experimental results of the digital predistortion of a class J PA are provided, demonstrating the proposal applicability in the attaining of the optimum number of coefficients. A comparison is made between the results obtained when the stopping rule is applied to the hill climbing (HC) and the doubly orthogonal matching pursuit (DOMP) algorithms

Modeling Approaches for Active Antenna Transmitters

The rapid growth of data traffic in mobile communications has attracted interest to Multiple-Input-Multiple-Output (MIMO) communication systems at millimeter-wave (mmWave) frequencies. MIMO systems exploit active antenna arrays transmitter configurations to obtain higher energy efficiency and beamforming flexibility. The analysis of transmitters in MIMO systems becomes complex due to the close integration of several antennas and power amplifiers (PAs) and the problems associated with heat dissipation. Therefore, the transmitter analysis requires efficient joint EM, circuit, and thermal simulations of its building blocks, i.e., the antenna array and PAs. Due to small physical spacing at mmWave, bulky isolators cannot be used to eliminate unwanted interactions between PA and antenna array. Therefore, the mismatch and mutual coupling in the antenna array directly affect PA output load and PA and transmitter performance. On the other hand, PAs are the primary source of nonlinearity, power consumption, and heat dissipation in transmitters. Therefore, it is crucial to include joint thermal and electrical behavior of PAs in analyzing active antenna transmitters. In this thesis, efficient techniques for modeling active antenna transmitters are presented. First, we propose a hardware-oriented transmitter model that considers PA load-dependent nonlinearity and the coupling, mismatch, and radiated field of the antenna array. The proposed model is equally accurate for any mismatch level that can happen at the PA output. This model can predict the transmitter radiation pattern and nonlinear signal distortions in the far-field. The model\u27s functionality is verified using a mmWave active subarray antenna module for a beam steering scenario and by performing the over-the-air measurements. The load-pull modeling idea was also applied to investigate the performance of a mmWave spatial power combiner module in the presence of critical coupling effects on combining performance. The second part of the thesis deals with thermal challenges in active antenna transmitters and PAs as the main source of heat dissipation. An efficient electrothermal modeling approach that considers the thermal behavior of PAs, including self-heating and thermal coupling between the IC hot spots, coupled with the electrical behavior of PA, is proposed. The thermal model has been employed to evaluate a PA DUT\u27s static and dynamic temperature-dependent performance in terms of linearity, gain, and efficiency. In summary, the proposed modeling approaches presented in this thesis provide efficient yet powerful tools for joint analysis of complex active antenna transmitters in MIMO systems, including sub-systems\u27 behavior and their interactions

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

Advanced signal processing techniques for the modeling and linearization of wireless communication systems.

Los nuevos estándares de comunicaciones digitales inalámbricas están impulsando el diseño de amplificadores de potencia con unas condiciones límites en términos de linealidad y eficiencia. Si bien estos nuevos sistemas exigen que los dispositivos activos trabajen cerca de la zona de saturación en busca de la eficiencia energética, la no linealidad inherente puede producir que el sistema muestre prestaciones inadecuadas en emisiones fuera de banda y distorsión en banda. La necesidad de técnicas digitales de compensación y la evolución en el diseño de nuevas arquitecturas de procesamiento de señales digitales posicionan a la predistorsión digital (DPD) como un enfoque práctico. Los predistorsionadores digitales se suelen basar en modelos de comportamiento como el memory polynomial (MP), el generalized memory polynomial (GMP) y el dynamic deviation reduction-based (DDR), etc. Los modelos de Volterra sufren la llamada "maldición de la dimensionalidad", ya que su complejidad tiende a crecer de forma exponencial a medida que el orden y la profundidad de memoria crecen. Esta tesis se centra principalmente en contribuir a la rama de conocimiento que enmarca el modelado y linealización de sistemas de comunicación inalámbrica. Los principales temas tratados son el modelo Volterra-Parafac y el modelo general de Volterra para sistemas complejos, los cuales tratan la estructura del DPD y las series de Volterra estructuradas con compressed-sensing y un método para la linealización en un rango de potencias de operación, que se centran en cómo los coeficientes de los modelos deben ser obtenidos.Premio Extraordinario de Doctorado U