<p><span>This book provides the analytical tools to characterize nonlinear distorted multicarrier signals and optimal/sub-optimal receivers employed in high data rate communication systems.</span></p><p><span>Unified Theoretical Analysis of Nonlinear Multicarrier Schemes introduces new optimal and s
Unified Theoretical Analysis of Nonlinear Multicarrier Schemes
β Scribed by Paulo Montezuma, JoΓ£o Guerreiro, Rui Dinis
- Publisher
- CRC Press
- Year
- 2024
- Tongue
- English
- Leaves
- 241
- Edition
- 1
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Synopsis
This book provides the analytical tools to characterize nonlinear distorted multicarrier signals and optimal/sub-optimal receivers employed in high data rate communication systems.
Unified Theoretical Analysis of Nonlinear Multicarrier Schemes introduces new optimal and sub-optimal receivers for nonlinear distorted signals that can use nonlinear distortion to improve performance when compared with common receivers. It addresses the analysis of nonlinear systems with stochastic inputs and establishes new receivers designs for multi-carrier communication systems with nonlinearities. The authors also include the characterization and definition of optimum and sub-optimum receivers for nonlinear distorted signals that may use the nonlinear distortion to improve receiver performance over the existing ones. The book also includes a set of applications where the analytical unified method for characterization of nonlinear distortion can be applied. The two final chapters of the book include systems like MIMO OFDM and the extension to optical systems. These techniques are the base of 5G, Wi-fi and future 6G mobile networks.
The book will be a valuable resource for design engineers, industrial engineers, applications engineers and researchers working on multi-carrier systems, power amplifiers modelling and design.
β¦ Table of Contents
Cover
Half Title
Title Page
Copyright Page
Dedication
Contents
Preface
Authors
List of Acronyms
Chapter 1: Introduction
1.1. Scope and Motivation
1.2. Book structure
Chapter 2: Multicarrier Systems
2.1. Historical Perspective
2.2. OFDM
2.2.1. Time and Frequency-Domain Characterization
2.2.2. Transmission over Frequency-Selective Channels
2.3. PAPR Problem
2.3.1. Amplification Issues
2.3.2. PAPR Reducing Techniques
Chapter 3: Nonlinear Distortion in Multicarrier Systems
3.1. Memoryless Nonlinearities
3.1.1. Baseband Nonlinearities
3.1.2. Bandpass Nonlinearities
3.2. Characterization of Nonlinearly Distorted Gaussian Signals
3.2.1. Baseband Multicarrier Signals
3.2.2. Bandpass Multicarrier Signals
3.3. Equivalent Nonlinearities
3.3.1. Baseband Equivalent Nonlinearities
3.3.2. Bandpass Equivalent Nonlinearities
Chapter 4: Optimum Detection of Nonlinear Multicarrier Schemes
4.1. Motivation and Conventional Approaches
4.2. Principle
4.3. Performance Analysis
4.3.1. Linear Multicarrier Schemes
4.3.2. Nonlinear Multicarrier Schemes
4.4. Theoretical Asymptotic Gains in AWGN Channels
4.4.1. Complex-valued Multicarrier Signals
4.4.2. Real-valued Multicarrier Signals
4.5. Theoretical Asymptotic Gains in Frequency-Selective Channels
Chapter 5: Applications
5.1. Conventional OFDM
5.1.1. Low-complexity Analytical Signalβs Characterization
5.1.2. Potential Optimum Performance
5.1.3. Sub-Optimum Detection
5.2. LINC Transmitters for OFDM Signals
5.3. Constant-Envelope OFDM
5.4. Amplify-and-Forward Relay OFDM Systems
Chapter 6: MIMO-OFDM and Optical OFDM Systems
6.1. MIMO and Massive MIMO-OFDM
6.2. DMT
6.3. Optical OFDM
6.3.1. Coherent Optical OFDM
6.3.2. Optical Wireless OFDM
Chapter 7: Conclusions
Appendix A: Baseband Representation of Bandpass Nonlinearities
Appendix B: Distribution of the Optimum Asymptotic Gain in Frequency-Selective Channels
References
Index
π SIMILAR VOLUMES
""The presentation is always clear and several examples and figures facilitate an easy understanding of all the techniques. The book can be used as a textbook in advanced undergraduate courses in multivariate analysis, and can represent a valuable reference manual for biologists and engineers workin
"Multivariate techniques are used to analyze data that arise from more than one variable in which there are relationships between the variables. Mainly based on the linearity of observed variables, these techniques are useful for extracting information and patterns from multivariate data as well as