Book contents
- Frontmatter
- Contents
- Preface
- List of Abbreviations
- List of Notation
- 1 Overview of Wireless Communications
- 2 Path Loss and Shadowing
- 3 Statistical Multipath Channel Models
- 4 Capacity of Wireless Channels
- 5 Digital Modulation and Detection
- 6 Performance of Digital Modulation over Wireless Channels
- 7 Diversity
- 8 Coding for Wireless Channels
- 9 Adaptive Modulation and Coding
- 10 Multiple Antennas and Space-Time Communications
- 11 Equalization
- 12 Multicarrier Modulation
- 13 Spread Spectrum
- 14 Multiuser Systems
- 15 Cellular Systems and Infrastructure-Based Wireless Networks
- 16 Ad Hoc Wireless Networks
- Appendix A Representation of Bandpass Signals and Channels
- Appendix B Probability Theory, Random Variables, and Random Processes
- Appendix C Matrix Definitions, Operations, and Properties
- Appendix D Summary of Wireless Standards
- Bibliography
- Index
9 - Adaptive Modulation and Coding
Published online by Cambridge University Press: 05 June 2012
- Frontmatter
- Contents
- Preface
- List of Abbreviations
- List of Notation
- 1 Overview of Wireless Communications
- 2 Path Loss and Shadowing
- 3 Statistical Multipath Channel Models
- 4 Capacity of Wireless Channels
- 5 Digital Modulation and Detection
- 6 Performance of Digital Modulation over Wireless Channels
- 7 Diversity
- 8 Coding for Wireless Channels
- 9 Adaptive Modulation and Coding
- 10 Multiple Antennas and Space-Time Communications
- 11 Equalization
- 12 Multicarrier Modulation
- 13 Spread Spectrum
- 14 Multiuser Systems
- 15 Cellular Systems and Infrastructure-Based Wireless Networks
- 16 Ad Hoc Wireless Networks
- Appendix A Representation of Bandpass Signals and Channels
- Appendix B Probability Theory, Random Variables, and Random Processes
- Appendix C Matrix Definitions, Operations, and Properties
- Appendix D Summary of Wireless Standards
- Bibliography
- Index
Summary
Adaptive modulation and coding enable robust and spectrally efficient transmission over time-varying channels. The basic premise is to estimate the channel at the receiver and feed this estimate back to the transmitter, so that the transmission scheme can be adapted relative to the channel characteristics. Modulation and coding techniques that do not adapt to fading conditions require a fixed link margin to maintain acceptable performance when the channel quality is poor. Thus, these systems are effectively designed for worst-case channel conditions. Since Rayleigh fading can cause a signal power loss of up to 30 dB, designing for the worst-case channel conditions can result in very inefficient utilization of the channel. Adapting to the channel fading can increase average throughput, reduce required transmit power, or reduce average probability of bit error by taking advantage of favorable channel conditions to send at higher data rates or lower power – and by reducing the data rate or increasing power as the channel degrades. In Section 4.2.4 we derived the optimal adaptive transmission scheme that achieves the Shannon capacity of a flat fading channel. In this chapter we describe more practical adaptive modulation and coding techniques to maximize average spectral efficiency while maintaining a given average or instantaneous bit error probability. The same basic premise can be applied to MIMO channels, frequency-selective fading channels with equalization, OFDM or CDMA, and cellular systems.
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- Wireless Communications , pp. 283 - 320Publisher: Cambridge University PressPrint publication year: 2005
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