Channel Equalization for Wireless Communications: From Concepts to Detailed Mathematics
The most thorough, up-to-date reference on channel equalization-from basic concepts to complex modeling techniques In today's instant-access society, a high premium is placed on information that can be stored and communicated effectively. As a result, storage densities and communications rates are being pushed to capacity, causing information symbols to interfere with one another. To help unclog pathways for the clearer conveyance of information, this book offers in-depth discussion of the sign…
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- Full title :Channel Equalization for Wireless Communications : From Concepts to Detailed Mathematics.
Summary
The most thorough, up-to-date reference on channel equalization-from basic concepts to complex modeling techniques In today's instant-access society, a high premium is placed on information that can be stored and communicated effectively. As a result, storage densities and communications rates are being pushed to capacity, causing information symbols to interfere with one another. To help unclog pathways for the clearer conveyance of information, this book offers in-depth discussion of the significant contributions and future adaptability of channel equalization and a set of approache.
Read More ↓Edition Statements
- Publication Date:2011.
Publication Statements
- Publisher(s):Wiley
- Place of Publication:Hoboken
- Language:eng
- Publication Date:2011.
Notes
7.2.2 Soft information.
The Physical Object
- Description:1 online resource (250 pages).
Edition Identifiers
- ISBN:1118105281, 9781118105283, 0470874279, 9780470874271, 9781118105252, 1118105257, 9781118105276, 1118105273, 9781118105269, 1118105265
- oclc:ocn990667965
- LC Classification:TK5103.2
- Dewey Decimal:621.382
Table of Contents
Channel Equalization for Wireless Communications: From Concepts to Detailed Mathematics; CONTENTS; List of Figures; List of Tables; Preface; Acknowledgments; Acronyms; 1 Introduction; 1.1 The Idea; 1.2 More Details; 1.2.1 General dispersive and MIMO scenarios; 1.2.2 Use of complex numbers; 1.3 The Math; 1.3.1 Transmitter; 1.3.2 Channel; 1.3.3 Receiver; 1.4 More Math; 1.4.1 Transmitter; 1.4.2 Channel; 1.4.3 Receiver; 1.5 An Example; 1.5.1 Reference system and channel models; 1.6 The Literature; Problems; 2 Matched Filtering; 2.1 The Idea; 2.2 More Details; 2.2.1 General dispersive scenario.
2.2.2 MIMO scenario2.3 The Math; 2.3.1 Maximum-likelihood detection; 2.3.2 Output SNR and error rate performance; 2.3.3 TDM; 2.3.4 Maximum SNR; 2.3.5 Partial MF; 2.3.6 Fractionally spaced MF; 2.3.7 Whitened MF; 2.3.8 The matched filter bound (MFB); 2.3.9 MF in colored noise; 2.3.10 Performance results; 2.4 More Math; 2.4.1 Partial MF; 2.4.2 The matched filter bound; 2.4.3 MF in colored noise; 2.4.4 Group matched filtering; 2.5 An Example; 2.6 The Literature; Problems; 3 Zero-Forcing Decision Feedback Equalization; 3.1 The Idea; 3.2 More Details; 3.3 The Math; 3.3.1 Performance results.
3.4 Mor…
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