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Digitally Enhanced Mixed Signal Systems /
The book comprises of 9 chapters and is devoted to digital enhancement techniques addressing key challenges relevant to analog, RF and mixed-signal components. This topic has emerged in the near past in the context of steadily shrinking CMOS technology, user increasing demand for higher flexibility...
| Clasificación: | Libro Electrónico |
|---|---|
| Otros Autores: | , , |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Stevenage :
Institution of Engineering & Technology,
2019.
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| Colección: | Materials, circuits and devices series ;
40. |
| Temas: | |
| Acceso en línea: | Texto completo |
Tabla de Contenidos:
- Intro; Contents; Preface; 1. Digitally enhanced mixed signal systems-the big picture / Christian Vogel, Harald Enzinger, and Karl Freiberger; 1.1 Motivation; 1.2 Methodology; 1.2.1 A system-oriented perspective; 1.2.2 An extended view on data converters; 1.2.3 The design process; 1.3 Examples; 1.3.1 Enhancing power amplifiers; 1.3.2 Enhancing data converters; 1.3.3 Enhancing clock generation; 1.4 Conclusion; References; 2. Nonlinear modeling / Raphael Vansebrouck, Dang-Kièn Germain Pham, Chadi Jabbour, and Patricia Desgreys; 2.1 Introduction; 2.2 Nonlinear models; 2.2.1 Parametric models
- 2.2.2 Nonparametric models; 2.3 Suited models for each RF bloc; 2.3.1 Extension to complex models; 2.3.2 Models for power amplifiers; 2.3.3 Models for low-noise amplifiers; 2.3.4 Models for baseband blocks; 2.4 Digital compensation of nonlinear distortions; 2.4.1 Direct learning architecture; 2.4.2 Indirect learning architecture; 2.5 Summary; References; 3. Digital predistortion / Geneviève Baudoin, Olivier Venard, and Dang-Kièn Germain Pham; 3.1 Why do we need predistortion?; 3.1.1 Waveform features; 3.1.2 System level considerations; 3.2 Principles of predistortion
- 3.3 Analog vs digital predistortion; 3.4 Mathematical aspects; 3.4.1 Baseband formulation; 3.4.2 pth-Order inverse of linear system; 3.5 Models for DPD structures; 3.5.1 Parametric models; 3.5.2 Nonparametric models; 3.6 Identification; 3.6.1 Indirect learning architecture; 3.6.2 Direct learning architecture; 3.6.3 DPD with iterative learning control (ILC); 3.7 Wideband and subband processing; 3.8 Multidimensional predistortion; 3.8.1 Linearization of noncontiguous carrier aggregation; 3.8.2 Multiple input multiple output; 3.9 Model sizing; 3.9.1 Model sizing by hill climbing heuristic
- 3.9.2 Model sizing by integer genetic algorithm; 3.9.3 Model sizing using orthogonal matching pursuit (OMP) algorithm; 3.10 Joint mitigation of various impairments; 3.10.1 Cooperation with crest factor reduction (CFR); 3.10.2 Processing of imperfections; 3.11 Overview of companion signal processing; 3.11.1 Synchronization; 3.11.2 Sampling frequency; 3.11.3 Monitoring; 3.12 Implementation; 3.13 Conclusion; References
- 4. Digital post-distortion of radio receivers and analog-to-digital converters / Bryce Minger, Raphaël Vansebrouck, Chadi Jabbour, Loïc Fuché, Guillaume Ferré, Dominique Dallet, Patricia Desgreys, and Olivier Jamin; 4.1 Motivations for post-distortion of radio receivers and ADCs; 4.1.1 Ideal vs. practical radio receiver; 4.1.2 Dynamic range issues of modern radio receivers; 4.1.3 Principle of post-distortion; 4.1.4 Figures of merit; 4.2 Review of distortions issues met in radio receivers; 4.2.1 Distortion issue of IF-digitising superheterodyne receivers