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

Reduced-complexity Digital Predistortion in Flexible Radio Spectrum Access

Wireless communications is nowadays seen as one of the main foundations of technological advancements in, e.g., healthcare, education, agriculture, transportation, computing, personal communications, media, and entertainment. This requires major technological developments and advances at different levels of the wireless communication systems and networks. In particular, it is required to utilize the currently available frequency spectrum in a more and more efficient way, while also adopting new spectral bands. Moreover, it is required that cheaper and smaller electronic components are used to build future wireless communication systems to facilitate increasingly cost-effective solutions. Meanwhile, energy efficiency becomes extremely important in wide scale deployments of the networks both from a running cost point of view, and from an environmental impact point of view. This is the big picture, or the so called ‘bird’s eye view’ of the challenges that are yet to be met in this very interesting and fast developing field of science.The power amplifier (PA) is the most power-hungry component in most RF transmitters. Consequently, its energy efficiency significantly contributes to the overall energy efficiency of the transmitter, and in fact the whole wireless network. Unfortunately, energy efficiency enhancement implies operating the PA closer to its saturation region, which typically results in severe nonlinear distortion that can deteriorate the signal quality and cause interference to neighboring users, both of which negatively impact the system spectral efficiency. Moreover, in flexible spectrum access scenarios, which are essential for improving the spectral efficiency, particular in the form of non-contiguous radio spectrum access, the nonlinear distortion due to the PA becomes even more severe and can significantly impact the overall network performance. For example, in noncontiguous carrier aggregation (CA) in LTE-Advanced, it has been demonstrated that in addition to the classical in-band distortion and regrowth around the main carriers, harmful spurious emission components are generated which can easily violate the spurious emission limits even in the case of user equipment (UE) transmitters.Technological advances in the digital electronics domain have enabled us to approach this problem from a digital signal processing point of view in the form of widely-adopted and researched digital predistortion (DPD) technology. However, when the signal bandwidth gets larger, and flexible or non-contiguous spectrum access is introduced, the complexity of the DPD increases and the power consumed in the digital domain by the DPD itself becomes higher and higher, to the extent that it might be close to, or even surpass, the energy savings achieved from using a more efficient PA. The problem becomes even more challenging at the UE side which has relatively limited computational capabilities and lower transmit power. This dilemma can be resolved by developing novel reduced-complexity DPD solutions in such flexible spectrum access and/or wide bandwidth scenarios while not sacrificing the DPD performance, which is the main topic area that this thesis work contributes to.The first contribution of this thesis is the development of a spur-injection based sub-band DPD structure for spurious emission mitigation in noncontiguous transmission scenarios. A novel and effective learning algorithm is also introduced, for the proposed sub-band DPD, based on the decorrelation principle. Mathematical models of the unwanted emissions are formulated based on realistic PA models with memory, followed by developing an efficient DPD structure for mitigating these emissions with reducedcomplexity in both the DPD main processing and learning paths while providing excellent spurious emission suppression. In the special case when the spurious emissions overlap with the own RX band in frequency division duplexing (FDD) transceivers, a novel subband DPD solution is also developed that uses the main RX for DPD learning without requiring any additional observation RX, thus further reducing the DPD complexity.The second contribution is the development of a novel reduced-complexity concurrent DPD, with a single-feedback receiver path, for carrier aggregation-like scenarios. The proposed solution is based on a simple and flexible DPD structure with decorrelationbased parameter learning. Practical simulations and RF measurements demonstrate that the proposed concurrent DPD provides excellent linearization performance, in terms of in-band error vector magnitude (EVM) and adjacent channel leakage ratio (ACLR), when compared to state-of-the-art concurrent DPD solutions, despite its reduced computational complexity in both the DPD main path processing and parameter learning.The third contribution is the development of a new and novel frequency-optimized DPD solution which can tailor its linearization capabilities to any particular regions of the spectrum. Detailed mathematical expressions of the power spectrum at the PA output as a function of the DPD coefficients are formulated. A Newton-Raphson optimization routine is then utilized to optimize the suppression of unwanted emissions at arbitrary pre-specified frequencies at the PA output. From a complexity reduction perspective, this means that for a given linearization performance at a particular frequency range, an optimized and reduced-complexity DPD can be used.Detailed quantitative complexity analysis, of all the proposed DPD solutions, is performed in this thesis. The complexity and linearization performance are also compared to state-of-the-art DPD solutions in the literature to validate and demonstrate the complexity reduction aspect without sacrificing the linearization performance. Moreover, all the DPD solutions developed in this thesis are tested in practical RF environments using real cellular power amplifiers that are commercially used in the latest wireless communication systems, both at the base station side and at the mobile terminal side. These experiments, along with the strong theoretical foundation of the developed DPD solutions prove that they can be commercially used as such to enhance the performance, energy efficiency, and cost effectiveness of next generation wireless transmitters

An agile supply modulator with improved transient performance for power efficient linear amplifier employing envelope tracking techniques

This article presents an agile supply modulator with optimal transient performance that includes improvement in rise time, overshoot and settling time for the envelope tracking supply in linear power amplifiers. For this purpose, we propose an on-demand current source module: the bang-bang transient performance enhancer (BBTPE). Its objective is to follow fast variations in input signals with reduced overshoot and settling time without deteriorating the steady-state performance of the buck regulator. The proposed approach enables fast system response through the BBTPE and an accurate steady-state output response through a low switching ripple and power efficient dynamic buck regulator. Fast output response with the help of the added module induces a slower rise of inductor current in the buck converter that further helps the proposed system to reduce both overshoot and settling time. This article also introduces an efficient selective tracking of envelope signal for linear PAs. To demonstrate the feasibility of the proposed solution, extensive simulations and experimental results from a discrete system are reported. The proposed supply modulator shows 80% improvement in rise time along with 60% reduction in both overshoot and settling time compared to the conventional dynamic buck regulator-based solution. Experimental results using the LTE 16-QAM 5 MHz standard shows improvement of 7.68 dB and 65.1% in adjacent channel power ratio (ACPR) and error vector magnitude (EVM), respectively.Peer ReviewedPostprint (author's final draft

Mitigation of nonlinear receiver effects in modern radar: advanced signal processing techniques

This thesis presents a study into nonlinearities in the radar receiver and investigates advanced digital signal processing (DSP) techniques capable of mitigating the resultant deleterious effects. The need for these mitigation techniques has become more prevalent as the use of commercial radar sensors has increased rapidly over the last decade. While advancements in low-cost radio frequency (RF) technologies have made mass-produced radar systems more feasible, they also pose a significant risk to the functionality of the sensor. One of the major compromises when employing low-cost commercial off-theshelf (COTS) components in the radar receiver is system linearity. This linearity trade-off leaves the radar susceptible to interfering signals as the RF receiver can now be driven into the weakly nonlinear regime. Radars are not designed to operate in the nonlinear regime as distortion is observed in the radar output if they do. If radars are to maintain operational performance in an RF environment that is becoming increasingly crowded, novel techniques that allow the sensor to operate in the nonlinear regime must be developed. Advanced DSP techniques offer a low-cost low-impact solution to the nonlinear receiver problem in modern radar. While there is very little work published on this topic in the radar literature, inspiration can be taken from the related field of communications where techniques have been successfully employed. It is clear from the communications literature that for any mitigation algorithm to be successful, the mechanisms driving the nonlinear distortion in the receiver must be understood in great detail. Therefore, a behavioural modelling technique capable of capturing both the nonlinear amplitude and phase effects in the radar receiver is presented before any mitigation techniques are studied. Two distinct groups of mitigation algorithms are then developed specifically for radar systems with their performance tested in the medium pulse repetition frequency (MPRF) mode of operation. The first of these is the look-up table (LUT) approach which has the benefit of being mode independent and computationally inexpensive to implement. The limitations of this communications-based technique are discussed with particular emphasis placed on its performance against receiver nonlinearities that exhibit complex nonlinear memory effects. The second group of mitigation algorithms to be developed is the forward modelling technique. While this novel technique is both mode dependent and computationally intensive to implement, it has a unique formalisation that allows it to be extended to include nonlinear memory effects in a well-defined manner. The performance of this forward modelling technique is analysed and discussed in detail. It was shown in this study that nonlinearities generated in the radar receiver can be successfully mitigated using advanced DSP techniques. For this to be the case however, the behaviour of the RF receiver must be characterised to a high degree of accuracy both in the linear and weakly nonlinear regimes. In the case where nonlinear memory effects are significant in the radar receiver, it was shown that memoryless mitigation techniques can become decorrelated drastically reducing their effectiveness. Importantly however, it was demonstrated that the LUT and forward modelling techniques can both be extended to compensate for complex nonlinear memory effects generated in the RF receiver. It was also found that the forward modelling technique dealt with the nonlinear memory effects in a far more robust manner than the LUT approach leading to a superior mitigation performance in the memory rich case