Formal deduction of a Volterra series model for complex-valued systems

This paper demonstrates a general model for nonlinear systems with complex-valued inputs and its application to communication systems modeling. Based on Wirtinger calculus and a double Volterra series approach, the proposed representation can also be considered as a generalization of the widely linear transformation to incorporate the description of nonlinear systems. The complete structure is pruned with the assistance of a compressive-sensing algorithm in order to reduce the number of parameters. To illustrate this approach, it has been experimentally implemented to model a transmitter for OFDM signals, which includes an I/Q modulator and a power amplifier.Ministerio de Economía y Competitividad TEC2014-53103-P

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

Transmitter Linearization Adaptable to Power-Varying Operation

This paper presents the design of a power-scalable digital predistorter (DPD) for transmitter architectures. The target is to accomplish the joint compensation of impairments due to the I/Q modulator and nonlinearities associated with the power amplifier, and procure a maintained linearization performance in a range of average working operation levels. The identification method for the linearizer parameters enriches the standard least-squares procedure with a synergistic integration with sparsity-based model pruning strategies. The method has been tested with a general complex-valued Volterra model applied to the linearization of two communications transmitters operating at 3.6 GHz. The linearizers designed for the two transmitters effectively provide the joint compensation of the nonlinear behavior. In addition to their good performance in terms of adjacent channel power ratio, the DPDs exhibit a wide range of power-varying adaptation.Comisión Interministerial de Ciencia y Tecnología (CICYT) TEC2014-53103-

Could we now convince Einstein?

The present conference takes place in the same year that celebrates the centenary of Albert Einstein. Hence it is a good occasion to reflect on those problems which have been at the core of Einstein's intellectual activity. Undoubtedly the foundation of quantum mechanics (QM) is one of these problems. It is known that Einstein was never convinced by the interpretation of quantum mechanics accepted, in his times and still now, by the majority of physicists. The fact that he was sharing this skepticism with people like Schrodinger and, most of all, the fact that no convincing answer, to the doubts of these people, had emerged in a more than half a century old debate, helped in keeping alive the attention of a growing number of people on this problem. The crucial issue is that the standard interpretation of QM has some physical implications which are experimentally verifiable and which, for several years, have been thought to be incompatible with relativity theory (the so-called "quantum nonlocality"). On the other hand alternative, more intuitive, interpretations (such as the ensemble interpretation) seemed to be ruled out from very well confirmed experimental data. The way out from this impasse has required a deep analysis of the connections between mathematics and physics as well as the emergence of new ideas both in mathematics (non-Kolmogorovian probabilities) and in physics (the theory of adaptive systems). The Einstein centenary is a good occasion for a short survey of these developments with the goal of answering the intriguing question posed in the title of the present paper

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

Amplifier Nonlinear Modeling with RF Pulses

This paper proposes a Volterra kernel identification procedure for wireless amplifiers with nonlinear memory. The technique is based on a reduced-order Volterra model for wideband amplifiers that is favorably compared with widely used memory polynomial model in terms of normalized mean square error. The identification method takes advantage of the particular model structure and is thoroughly derived with a proper selection of pulse-like waveforms of known amplitude as probing signals with special emphasis on the extraction of the fifth-order kernel. The main advantage of the method is that it allows exploring the dynamic range of the amplifier without rising the temperature in the device or altering the biasing point. For validation purposes, a commercial amplifier has been characterized and the extracted kernels have been used to predict the response under wideband code-division multiple-access-like signals. In addition to the simplicity of the deterministic approach used in this extraction procedure, the agreement of the predicted responses with measurements was highly satisfactory in all cases and permitted the capture of phenomena that are due to nonlinear memory effects.CICYT TEC2004-06451-C05-03Junta de Andalucía Grant P07-TIC-0264

Volterra Behavioral Model for Wideband RF Amplifiers

This paper proposes a behavioral modeling approach for the description of nonlinearities in wideband wireless communication circuits with memory. The model is formally derived exploiting the dependence on frequency of the amplifier nonlinear transfer functions and reduce the number of parameters in a general Volterra-based behavioral model. To validate the proposed approach, a commercial amplifier at 915 MHz, exhibiting nonlinear memory effects, has been widely characterized using different stimuli, including two tones, quadrature phase-shift keying wideband code division multiple access, and 16-quadrature amplitude modulation signals with rectangular and root-raised cosine conforming pulses. The theoretical results have been compared with experimental data demonstrating that the model performance is comparable to the well-established memory polynomial model. Calculated and measured baseband waveforms, signal constellation, spectral regrowth and adjacent channel power ratio are tightly coincident in all cases, emphasizing the relevance of the proposed modelCICYT TEC2004-06451-C05-0

Sparse identification of volterra models for power amplifiers without pseudoinverse computation

Article number 9178996We present a new formulation of the doubly orthogonal matching pursuit (DOMP) algorithm for the sparse recovery of Volterra series models. The proposal works over the covariance matrices by taking advantage of the orthogonal properties of the solution at each iteration and avoids the calculation of the pseudoinverse matrix to obtain the model coefficients. A detailed formulation of the algorithm is provided along with a computational complexity assessment, showing a fixed complexity per iteration compared with its previous versions in which it depends on the iteration number. Moreover, we empirically demonstrate the reduction in computational complexity in terms of runtime and highlight the pruning capabilities through its application to the digital predistortion of a class J power amplifier operating under 5G-NR signals with the bandwidth of 20 and 30 MHz, concluding that this proposal significantly outperforms existing techniques in terms of computational complexity