Book contents
- Frontmatter
- Contents
- List of figures
- List of tables
- Preface
- List of symbols
- List of abbreviations
- 1 Introduction
- I ISI channels and adaptive signal processing
- II Iterative signal processing for ISI channels
- III Other interference-limited systems
- Appendix 1 Review of signal processing and the Ƶ-transform
- Appendix 2 Important properties of matrices and vectors
- Appendix 3 Background for probability and statistics
- References
- Index
Preface
Published online by Cambridge University Press: 23 November 2009
- Frontmatter
- Contents
- List of figures
- List of tables
- Preface
- List of symbols
- List of abbreviations
- 1 Introduction
- I ISI channels and adaptive signal processing
- II Iterative signal processing for ISI channels
- III Other interference-limited systems
- Appendix 1 Review of signal processing and the Ƶ-transform
- Appendix 2 Important properties of matrices and vectors
- Appendix 3 Background for probability and statistics
- References
- Index
Summary
Various signal processing techniques are actively used in communication systems to improve the performance. In particular, adaptive signal processing has a strong impact on communications. For example, various adaptive algorithms are applied to the channel equalization and interference rejection. Adaptive equalizers and interference cancellers can effectively mitigate interference and adapt to time-varying channel environments.
Even though iterative signal processing is not as advanced as adaptive signal processing, it plays a significant role in improving the performance of receivers, which may be limited by interfering signals. In addition, the estimation error of certain channel parameters, for example the channel impulse response, can degrade the performance. An improvement in interference cancelation or a better estimate of channel parameters may be available due to iterative signal processing. After each iteration, more information about interfering signals or channel parameters is available. Then, the interference cancelation is more precise and the channel parameters can be estimated more accurately. This results in an improvement in performance for each iteration.
It would be beneficial if we could study adaptive and iterative signal processing with respect to communications. There are a number of excellent books on adaptive signal processing and communication systems, though it is difficult to find a single book that covers both topics in detail. Furthermore, as iterative signal processing is less advanced, I have been unable to find a book that balances the subjects of signal processing and its applications in communication. My desire to locate such a book increased when I took a postgraduate course entitled “Adaptive Signal Processing in Telecommunications.”
- Type
- Chapter
- Information
- Adaptive and Iterative Signal Processing in Communications , pp. xiii - xivPublisher: Cambridge University PressPrint publication year: 2006