 Название: Interleaving Concepts for Digital-to-Analog Converters: Algorithms, Models, Simulations and Experiments
Автор: Christian Schmidt
Издательство: Springer Vieweg
Год: 2019 (2020 Edition)
Страниц: 268
Язык: английский
Формат: pdf (true), djvu
Размер: 10.1 MB
The infrastructure for tomorrow’s information and communication technology (ICT) requires not only higher bandwidth but also more energy-efficient data communications to accommodate the increasing amount of data traffic. For this, optical data transmission is the key technology. Important components are the data converters performing the transformation between the digital and the analog domain and vice versa. Digital-to-analog converters (DACs) and analog-to-digital converters (ADCs) enable the utilization of real-time digital signal processing (DSP) for software-defined waveforms with both flexible modulation bandwidth and modulation formats, improved coding techniques as well as pre- and post-equalization possibilities.
Modern complementary metal oxide semiconductor (CMOS) digital-to-analog converters (DACs) are limited in their bandwidth due to technological constraints. These limitations can be overcome by parallel DAC architectures, which are called interleaving concepts. Christian Schmidt analyzes the limitations and the potential of two innovative DAC interleaving concepts to provide the basis for a practical implementation: the analog multiplexing DAC (AMUX-DAC) and the frequency interleaving DAC (FI-DAC). He presents analytical and discrete-time models as a theoretical foundation and develops digital signal processing (DSP) algorithms to compensate the analog impairments. Further, he quantifies the impact of various limiting parameters with numerical simulations and verifies both concepts in laboratory experiments.
Contents:
- DAC Fundamentals and Interleaving Concepts
- Time Interleaving DAC
- Analog Multiplexing DAC
- Frequency Interleaving DAC
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Interleaving Concepts for Digital-to-Analog Converters: Algorithms, Models, Simulations and Experiments 
