Sparse Nonlinear MIMO Filtering and Identification

In this chapter system identification algorithms for sparse nonlinear multi input multi output (MIMO) systems are developed. These algorithms are potentially useful in a variety of application areas including digital transmission systems incorporating power amplifier(s) along with multiple antennas, cognitive processing, adaptive control of nonlinear multivariable systems, and multivariable biological systems. Sparsity is a key constraint imposed on the model. The presence of sparsity is often dictated by physical considerations as in wireless fading channel-estimation. In other cases it appears as a pragmatic modelling approach that seeks to cope with the curse of dimensionality, particularly acute in nonlinear systems like Volterra type series. Three dentification approaches are discussed: conventional identification based on both input and output samples, semi–blind identification placing emphasis on minimal input resources and blind identification whereby only output samples are available plus a–priori information on input characteristics. Based on this taxonomy a variety of algorithms, existing and new, are studied and evaluated by simulation

Iterative pre-distortion of the non-linear satellite channel

Digital Video Broadcasting - Satellite - Second Generation (DVB-S2) is the current European standard for satellite broadcast and broadband communications. It relies on high order modulations up to 32-amplitude/phase-shift-keying (APSK) in order to increase the system spectral efficiency. Unfortunately, as the modulation order increases, the receiver becomes more sensitive to physical layer impairments, and notably to the distortions induced by the power amplifier and the channelizing filters aboard the satellite. Pre-distortion of the non-linear satellite channel has been studied for many years. However, the performance of existing pre-distortion algorithms generally becomes poor when high-order modulations are used on a non-linear channel with a long memory. In this paper, we investigate a new iterative method that pre-distorts blocks of transmitted symbols so as to minimize the Euclidian distance between the transmitted and received symbols. We also propose approximations to relax the pre-distorter complexity while keeping its performance acceptable

Linear and nonlinear room compensation of audio rendering systems

[EN] Common audio systems are designed with the intent of creating real and immersive scenarios that allow the user to experience a particular acoustic sensation that does not depend on the room he is perceiving the sound. However, acoustic devices and multichannel rendering systems working inside a room, can impair the global audio effect and thus the 3D spatial sound. In order to preserve the spatial sound characteristics of multichannel rendering techniques, adaptive filtering schemes are presented in this dissertation to compensate these electroacoustic effects and to achieve the immersive sensation of the desired acoustic system. Adaptive filtering offers a solution to the room equalization problem that is doubly interesting. First of all, it iteratively solves the room inversion problem, which can become computationally complex to obtain when direct methods are used. Secondly, the use of adaptive filters allows to follow the time-varying room conditions. In this regard, adaptive equalization (AE) filters try to cancel the echoes due to the room effects. In this work, we consider this problem and propose effective and robust linear schemes to solve this equalization problem by using adaptive filters. To do this, different adaptive filtering schemes are introduced in the AE context. These filtering schemes are based on three strategies previously introduced in the literature: the convex combination of filters, the biasing of the filter weights and the block-based filtering. More specifically, and motivated by the sparse nature of the acoustic impulse response and its corresponding optimal inverse filter, we introduce different adaptive equalization algorithms. In addition, since audio immersive systems usually require the use of multiple transducers, the multichannel adaptive equalization problem should be also taken into account when new single-channel approaches are presented, in the sense that they can be straightforwardly extended to the multichannel case. On the other hand, when dealing with audio devices, consideration must be given to the nonlinearities of the system in order to properly equalize the electroacoustic system. For that purpose, we propose a novel nonlinear filtered-x approach to compensate both room reverberation and nonlinear distortion with memory caused by the amplifier and loudspeaker devices. Finally, it is important to validate the algorithms proposed in a real-time implementation. Thus, some initial research results demonstrate that an adaptive equalizer can be used to compensate room distortions.[ES] Los sistemas de audio actuales están diseñados con la idea de crear escenarios reales e inmersivos que permitan al usuario experimentar determinadas sensaciones acústicas que no dependan de la sala o situación donde se esté percibiendo el sonido. Sin embargo, los dispositivos acústicos y los sistemas multicanal funcionando dentro de salas, pueden perjudicar el efecto global sonoro y de esta forma, el sonido espacial 3D. Para poder preservar las características espaciales sonoras de los sistemas de reproducción multicanal, en esta tesis se presentan los esquemas de filtrado adaptativo para compensar dichos efectos electroacústicos y conseguir la sensación inmersiva del sistema sonoro deseado. El filtrado adaptativo ofrece una solución al problema de salas que es interesante por dos motivos. Por un lado, resuelve de forma iterativa el problema de inversión de salas, que puede llegar a ser computacionalmente costoso para los métodos de inversión directos existentes. Por otro lado, el uso de filtros adaptativos permite seguir las variaciones cambiantes de los efectos de la sala de escucha. A este respecto, los filtros de ecualización adaptativa (AE) intentan cancelar los ecos introducidos por la sala de escucha. En esta tesis se considera este problema y se proponen esquemas lineales efectivos y robustos para resolver el problema de ecualización mediante filtros adaptativos. Para conseguirlo, se introducen diferentes esquemas de filtrado adaptativo para AE. Estos esquemas de filtrado se basan en tres estrategias ya usadas en la literatura: la combinación convexa de filtros, el sesgado de los coeficientes del filtro y el filtrado basado en bloques. Más especificamente y motivado por la naturaleza dispersiva de las respuestas al impulso acústicas y de sus correspondientes filtros inversos óptimos, se presentan diversos algoritmos adaptativos de ecualización específicos. Además, ya que los sistemas de audio inmersivos requieren usar normalmente múltiples trasductores, se debe considerar también el problema de ecualización multicanal adaptativa cuando se diseñan nuevas estrategias de filtrado adaptativo para sistemas monocanal, ya que éstas deben ser fácilmente extrapolables al caso multicanal. Por otro lado, cuando se utilizan dispositivos acústicos, se debe considerar la existencia de no linearidades en el sistema elactroacústico, para poder ecualizarlo correctamente. Por este motivo, se propone un nuevo modelo no lineal de filtrado-x que compense a la vez la reverberación introducida por la sala y la distorsión no lineal con memoria provocada por el amplificador y el altavoz. Por último, es importante validar los algoritmos propuestos mediante implementaciones en tiempo real, para asegurarnos que pueden realizarse. Para ello, se presentan algunos resultados experimentales iniciales que muestran la idoneidad de la ecualización adaptativa en problemas de compensación de salas.[CA] Els sistemes d'àudio actuals es dissenyen amb l'objectiu de crear ambients reals i immersius que permeten a l'usuari experimentar una sensació acústica particular que no depèn de la sala on està percebent el so. No obstant això, els dispositius acústics i els sistemes de renderització multicanal treballant dins d'una sala poden arribar a modificar l'efecte global de l'àudio i per tant, l'efecte 3D del so a l'espai. Amb l'objectiu de conservar les característiques espacials del so obtingut amb tècniques de renderització multicanal, aquesta tesi doctoral presenta esquemes de filtrat adaptatiu per a compensar aquests efectes electroacústics i aconseguir una sensació immersiva del sistema acústic desitjat. El filtrat adaptatiu presenta una solució al problema d'equalització de sales que es interessant baix dos punts de vista. Per una banda, el filtrat adaptatiu resol de forma iterativa el problema inversió de sales, que pot arribar a ser molt complexe computacionalment quan s'utilitzen mètodes directes. Per altra banda, l'ús de filtres adaptatius permet fer un seguiment de les condicions canviants de la sala amb el temps. Més concretament, els filtres d'equalització adaptatius (EA) intenten cancel·lar els ecos produïts per la sala. A aquesta tesi, considerem aquest problema i proposem esquemes lineals efectius i robustos per a resoldre aquest problema d'equalització mitjançant filtres adaptatius. Per aconseguir-ho, diferent esquemes de filtrat adaptatiu es presenten dins del context del problema d'EA. Aquests esquemes de filtrat es basen en tres estratègies ja presentades a l'estat de l'art: la combinació convexa de filtres, el sesgat dels pesos del filtre i el filtrat basat en blocs. Més concretament, i motivat per la naturalesa dispersa de la resposta a l'impuls acústica i el corresponent filtre òptim invers, presentem diferents algorismes d'equalització adaptativa. A més a més, com que els sistemes d'àudio immersiu normalment requereixen l'ús de múltiples transductors, cal considerar també el problema d'equalització adaptativa multicanal quan es presenten noves solucions de canal simple, ja que aquestes s'han de poder estendre fàcilment al cas multicanal. Un altre aspecte a considerar quan es treballa amb dispositius d'àudio és el de les no linealitats del sistema a l'hora d'equalitzar correctament el sistema electroacústic. Amb aquest objectiu, a aquesta tesi es proposa una nova tècnica basada en filtrat-x no lineal, per a compensar tant la reverberació de la sala com la distorsió no lineal amb memòria introduïda per l'amplificador i els altaveus. Per últim, és important validar la implementació en temps real dels algorismes proposats. Amb aquest objectiu, alguns resultats inicials demostren la idoneïtat de l'equalització adaptativa en problemes de compensació de sales.Fuster Criado, L. (2015). Linear and nonlinear room compensation of audio rendering systems [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/5945

Multiple-input multiple-output symbol rate signal digital predistorter for non-linear multi-carrier satellite channels

Abstract: A digital predistortion (DPD) scheme is presented for non-linear distortion mitigation in multi-carrier satellite communication channels. The proposed DPD has a multiple-input multiple-output architecture similar to data DPD schemes. However, it enhances the mitigation performance of data DPDs using a multi-rate processing algorithm to achieve spectrum broadening of non-linear operators. Compared to single carrier (single-input single-output) signal (waveform) DPD schemes, the proposed DPD has lower digital processing rate reducing the required hardware cost of the predistorter. The proposed DPD outperforms, in total degradation, both data and signal DPD schemes. Further, it performs closest to a channel bound described by an ideally mitigated channel with limited maximum output power

Joint Satellite-Transmitter and Ground-Receiver Digital Pre-Distortion for Active Phased Arrays in LEO Satellite Communications

A novel joint satellite-transmitter and ground-receiver (JSG) digital pre-distortion (DPD) (JSG-DPD) technique is proposed to improve the linearity and power efficiency of the space-borne active phased arrays (APAs) in low Earth orbit (LEO) satellite communications. Different from the conventional DPD technique that requires a complex RF feedback loop, the DPD coefficients based on a generalized memory polynomial (GMP) model are extracted at the ground-receiver and then transmitted to the digital baseband front-end of the LEO satellite-transmitter via a satellite–ground bi-directional transmission link. The issue of the additive white Gaussian noise (AWGN) of the satellite–ground channel affecting the extraction of DPD coefficients is tackled using a superimposing training sequences (STS) method. The proposed technique has been experimentally verified using a 28 GHz phased array. The performance improvements in terms of error vector amplitude (EVM) and adjacent channel power ratio (ACPR) are 7.5% and 3.6 dB, respectively. Requiring limited space-borne resources, this technique offers a promising solution to achieve APA DPD for LEO satellite communications

An implementation of the redirected learning architecture for digital pre-distortion

Digital pre-distortion is a digital signal processing technique that\u27s used to linearize the output of various systems. A common application of digital pre-distortion is to linearize microwave power amplifier circuits, because non-linear distortion can lead to inefficient performance and out of band emissions. Since its conception, several different architectures have been developed for digital pre-distortion. There are online architectures, such as the indirect learning architecture, where signal processing is done while the amplifier is running. There are also offline architectures, such as the direct learning architecture and the relatively new redirected learning architecture, where the signal processing is done using previous input and output data from the amplifier to create a pre-distorted signal. The choice of which architecture to use often comes down to a trade off between performance and complexity. However, a common problem exists between these architectures; the complexity of the pre-distortion technique is bound to the complexity of the system\u27s architecture. Most digital pre-distortion systems in use today use Volterra series filters and their derivatives for behavioral modeling or simple look-up tables. The complexity of applying a given behavioral model to an input signal varies little between architectures, so for a given model the question becomes which architecture will yield the greatest performance. Online methods have excellent performance, though the system required to train the models is computationally complex, as the algorithms to implement them require many calculations in a short period of time; whereas offline methods do not require an expensive training system but may not perform as well. For this reason, it is often desirable to use offline methods to save on system costs and engineering time. Most offline digital pre-distortion systems use the direct learning architecture, however newer architectures may be able to outperform the direct learning architecture with a given behavioral model.In this thesis it is shown how the redirected learning architecture was used to mitigate harmonic distortion by about 30~dB more than the indirect learning architecture. The direct, indirect, and redirected learning architectures are presented, as well as various behavioral models. This is followed by an analysis of the redirected learning architecture. Finally an implementation of the redirected learning model is presented using ADS-Matlab co-simulation. The results are then discussed to show the potential of the redirected learning method

Nonlinear Equalization and Digital Pre-Distortion Techniques for Future Radar and Communications Digital Array Systems

Modern radar (military, automotive, weather, etc.) and communication systems seek to leverage the spatio-spectral efficiency of phased arrays. Specifically, there is an increasingly large demand for fully-digital arrays, with each antenna element having its own transmitter and receiver. Further, in order to makes these systems realizable, low-cost, low-complexity solutions are required, often sacrificing the system's linearity. Lower linearity paired with the inherent lack of RF spacial filtering can make these highly digital systems vulnerable to high-power interferering signals-- potentially introducing spectral regrowth and/or gain compression, distorting the signal-of-interest. Digital linearization solutions such as Digital Pre-Distiortion (DPD) and Nonlinear Equalization (NLEQ) have been shown to effectively mitigate nonlinearities for transmitters and receivers, respectively. Further, DPD and NLEQ seek to extend the effective dynamic range of digital arrays, helping the systems reach their designed dynamic range improvement of $10\log_{10}(N)$~dB, where $N$ is the number of transmitters/receivers. However, the performance of these solutions is ultimately determined by training model and waveform. Further, the nonlinear characteristics of a system can change with temperature, frequency, power, time, etc., requiring a robust calibration technique to maintain a high-level of nonlinear mitigation. This dissertation reviews the different types of nonlinear models and the current NLEQ and DPD algorithms for digital array systems. Further, a generalized calibration waveform for both NLEQ and DPD is proposed, allowing a system to maximize its dynamic range over power and frequency. Additionally, an \textit{in-situ} calibration method, leveraging the inherent mutual coupling in an array, is proposed as a solution to maintaining a high level of performance in a fielded digital array system over the system's lifetime. The combination of the proposed training waveform and \textit{in-situ} calibration technique prove to be very effective at adaptively creating a generalized solution to extending the dynamic range of future low-cost digital array systems

Analytical Characterization and Optimum Detection of Nonlinear Multicarrier Schemes

It is widely recognized that multicarrier systems such as orthogonal frequency division multiplexing (OFDM) are suitable for severely time-dispersive channels. However, it is also recognized that multicarrier signals have high envelope fluctuations which make them especially sensitive to nonlinear distortion effects. In fact, it is almost unavoidable to have nonlinear distortion effects in the transmission chain. For this reason, it is essential to have a theoretical, accurate characterization of nonlinearly distorted signals not only to evaluate the corresponding impact of these distortion effects on the system’s performance, but also to develop mechanisms to combat them. One of the goals of this thesis is to address these challenges and involves a theoretical characterization of nonlinearly distorted multicarrier signals in a simple, accurate way. The other goal of this thesis is to study the optimum detection of nonlinearly distorted, multicarrier signals. Conventionally, nonlinear distortion is seen as a noise term that degrades the system’s performance, leading even to irreducible error floors. Even receivers that try to estimate and cancel it have a poor performance, comparatively to the performance associated to a linear transmission, even with perfect cancellation of nonlinear distortion effects. It is shown that the nonlinear distortion should not be considered as a noise term, but instead as something that contains useful information for detection purposes. The adequate receiver to take advantage of this information is the optimum receiver, since it makes a block-by-block detection, allowing us to exploit the nonlinear distortion which is spread along the signal’s band. Although the optimum receiver for nonlinear multicarrier schemes is too complex, due to its necessity to compare the received signal with all possible transmitted sequences, it is important to study its potential performance gains. In this thesis, it is shown that the optimum receiver outperforms the conventional detection, presenting gains not only relatively to conventional receivers that deal with nonlinear multicarrier signals, but also relatively to conventional receivers that deal with linear, multicarrier signals. We also present sub-optimum receivers which are able to approach the performance gains associated to the optimum detection and that can even outperform the conventional linear, multicarrier schemes

Optics for AI and AI for Optics

Artificial intelligence is deeply involved in our daily lives via reinforcing the digital transformation of modern economies and infrastructure. It relies on powerful computing clusters, which face bottlenecks of power consumption for both data transmission and intensive computing. Meanwhile, optics (especially optical communications, which underpin today’s telecommunications) is penetrating short-reach connections down to the chip level, thus meeting with AI technology and creating numerous opportunities. This book is about the marriage of optics and AI and how each part can benefit from the other. Optics facilitates on-chip neural networks based on fast optical computing and energy-efficient interconnects and communications. On the other hand, AI enables efficient tools to address the challenges of today’s optical communication networks, which behave in an increasingly complex manner. The book collects contributions from pioneering researchers from both academy and industry to discuss the challenges and solutions in each of the respective fields

Design and Linearization of Energy Efficiency Power Amplifier in Nonlinear OFDM Transmitter for LTE-5G Applications. Simulation and measurements of energy efficiency power amplifier in the presence of nonlinear OFDM transmitter system and digital predistortion based on Hammerstein-Wiener method

This research work has made an effort to understand a novel line of radio frequency power amplifiers (RFPAs) that address initiatives for efficiency enhancement and linearity compensation to harmonize the fifth generation (5G) campaign. The objective is to enhance the performance of an orthogonal frequency division multiplexing-long term evolution (OFDM-LTE) transmitter by reducing the nonlinear distortion of the RFPA. The first part of this work explores the design and implementation of 15.5 W class AB RF power amplifier, adopting a balanced technique to stimulate efficiency enhancement and redeeming exhibition of excessive power in the transmitter. Consequently, this work goes beyond improving efficiency over a linear RF power amplifier design; in which a comprehensive investigation on the fundamental and harmonic components of class F RF power amplifier using a load-pull approach to realise an optimum load impedance and the matching network is presented. The frequency bandwidth for both amplifiers was allocated to operate in the 2.620-2.690 GHz of mobile LTE applications. The second part explores the development of the behavioural model for the class AB power amplifier. A particular novel, Hammerstein-Wiener based model is proposed to describe the dynamic nonlinear behaviour of the power amplifier. The RF power amplifier nonlinear distortion is approximated using a new linear parameter approximation approach. The first and second-order Hammerstein-Wiener using the Normalised Least Mean Square Error (NLMSE) algorithm is used with the aim of easing the complexity of filtering process during linear memory cancellation. Moreover, an enhanced adaptive Wiener model is proposed to explore the nonlinear memory effect in the system. The proposed approach is able to balance between convergence speed and high-level accuracy when compared with behavioural modelling algorithms that are more complex in computation. Finally, the adaptive predistorter technique is implemented and verified in the OFDM transceiver test-bed. The results were compared against the computed one from MATLAB simulation for OFDM and 5G modulation transmitters. The results have confirmed the reliability of the model and the effectiveness of the proposed predistorter.Fundacão para a Ciência e a Tecnologia, Portugal, under European Union’s Horizon 2020 research and innovation programme ... grant agreement H2020-MSCA-ITN- 2016 SECRET-722424 I also acknowledge the role of the National Space Research and Development Agency (NASRDA) Sokoto State Government Petroleum Technology Trust Fund (PTDF