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Look-Ahead Based Sigma-Delta Modulation [Kõva köide]

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  • Formaat: Hardback, 248 pages, kõrgus x laius: 235x155 mm, kaal: 580 g, XII, 248 p., 1 Hardback
  • Sari: Analog Circuits and Signal Processing
  • Ilmumisaeg: 07-Apr-2011
  • Kirjastus: Springer
  • ISBN-10: 940071386X
  • ISBN-13: 9789400713864
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Look-Ahead Based Sigma-Delta ModulationSuurem pilt
  • Formaat: Hardback, 248 pages, kõrgus x laius: 235x155 mm, kaal: 580 g, XII, 248 p., 1 Hardback
  • Sari: Analog Circuits and Signal Processing
  • Ilmumisaeg: 07-Apr-2011
  • Kirjastus: Springer
  • ISBN-10: 940071386X
  • ISBN-13: 9789400713864
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9789400713864.html
Märksõnad:
Aiming to expand our existing knowledge of discrete-time 1-bit look-ahead modulation, this volume analyzes potential improvements to digital noise-shaping look-ahead solutions. The results are expressed through the SA-CD lossless data compression algorithm.

The aim of this book is to expand and improve upon the existing knowledge on discrete-time 1-bit look-ahead sigma-delta modulation in general, and to come to a solution for the above mentioned specific issues arising from 1-bit sigma-delta modulation for SA-CD. In order to achieve this objective an analysis is made of the possibilities for improving the performance of digital noise-shaping look-ahead solutions. On the basis of the insights obtained from the analysis, several novel generic 1-bit look-ahead solutions that improve upon the state-of-the-art will be derived and their performance will be evaluated and compared. Finally, all the insights are combined with the knowledge of the SA-CD lossless data compression algorithm to come to a specifically for SA-CD optimized look-ahead design.
1 Introduction
1(4)
2 Basics of Sigma-Delta Modulation
5(24)
2.1 AD, DD, and DA Sigma-Delta Conversion
8(2)
2.1.1 AD Conversion
8(1)
2.1.2 DD Conversion
9(1)
2.1.3 DA Conversion
9(1)
2.2 Sigma-Delta Structures
10(2)
2.3 Linear Modeling of an SDM
12(5)
2.4 Sigma-Delta Modulator Performance Indicators
17(12)
2.4.1 Generic Converter Performance
17(5)
2.4.2 SDM Specific Functional Performance
22(4)
2.4.3 SDM Specific Implementation Costs
26(1)
2.4.4 Figure-of-Merit of an SDM
27(2)
3 Transient SDM Performance
29(14)
3.1 Measuring Signal Conversion Quality
29(2)
3.1.1 Steady-State
29(1)
3.1.2 Non-steady-State
30(1)
3.2 Time Domain SINAD Measurement
31(2)
3.3 Steady-State SINAD Measurement Analysis
33(4)
3.3.1 Obtaining the Linearized STF
34(3)
3.3.2 Time Domain SINAD Measurement
37(1)
3.4 Non-steady-State SINAD Measurement Analysis
37(3)
3.5 Conclusions
40(3)
4 Noise-Shaping Quantizer Model
43(6)
4.1 Generic Quantizer
43(1)
4.2 Noise-Shaping Quantizer
44(2)
4.3 Noise-Shaping Quantizer with Multiple Cost Functions
46(1)
4.4 Specific Realization Structures
47(2)
5 Look-Ahead Sigma-Delta Modulation
49(28)
5.1 Noise-Shaping Quantizer with Look-Ahead
49(2)
5.2 Look-Ahead Enabled SDM Model
51(1)
5.3 Look-Ahead Principle
52(3)
5.3.1 Quantizer Cost Function
54(1)
5.4 Obtaining Information About the Future
55(1)
5.4.1 Approximated Future Input
55(1)
5.4.2 Actual Future Input
56(1)
5.5 Full Look-Ahead Algorithm
56(3)
5.6 Linear Modeling of a Look-Ahead SDM
59(5)
5.6.1 Boundary Conditions and Assumptions
59(1)
5.6.2 Feed-Forward Look-Ahead SDM
60(2)
5.6.3 Feed-Back Look-Ahead SDM
62(2)
5.7 Benefits and Disadvantages of Look-Ahead
64(4)
5.7.1 Benefits
65(2)
5.7.2 Disadvantages
67(1)
5.8 Look-Ahead AD Conversion
68(4)
5.8.1 Potential Benefits and Disadvantages of Look-Ahead in AD Conversion
68(1)
5.8.2 Feasibility of a Look-Ahead ADC
69(2)
5.8.3 Hybrid Look-Ahead ADC
71(1)
5.8.4 Conclusion
72(1)
5.9 Look-Ahead DD Conversion
72(3)
5.10 Conclusions
75(2)
6 Reducing the Computational Complexity of Look-Ahead DD Conversion
77(26)
6.1 Full Look-Ahead
77(5)
6.1.1 Complete Response Calculation with Reuse of Intermediate Results
78(1)
6.1.2 Select and Continue with Half of the Solutions
78(1)
6.1.3 Linear Decomposition of the Filter Response
79(1)
6.1.4 Conditional Computation of the Solutions
80(1)
6.1.5 Calculating Multiple Output Symbols per Step
80(2)
6.1.6 Summary
82(1)
6.2 Pruned Look-Ahead
82(13)
6.2.1 Motivation for Pruning
83(1)
6.2.2 Basic Pruned Look-Ahead Modulation
84(2)
6.2.3 Pruned Look-Ahead Modulation with Reuse of Results
86(9)
6.2.4 Summary
95(1)
6.3 Pruned Look-Ahead Modulator Realizations
95(6)
6.3.1 Trellis Sigma-Delta Modulation
96(1)
6.3.2 Efficient Trellis Sigma-Delta Modulation
97(1)
6.3.3 Pruned Tree Sigma-Delta Modulation
98(2)
6.3.4 Pruned Tree Sigma-Delta Modulation for SA-CD
100(1)
6.4 Conclusions
101(2)
7 Trellis Sigma-Delta Modulation
103(34)
7.1 Algorithm --- Kato Model
104(5)
7.1.1 Hidden Markov Model
104(2)
7.1.2 Algorithm Steps
106(3)
7.2 Algorithm --- Pruned Look-Ahead Model
109(1)
7.3 Verification of the Linearized NTF and STF
110(3)
7.3.1 NTF
110(2)
7.3.2 STF
112(1)
7.4 Relation Trellis Order and Trellis Depth
113(6)
7.4.1 Simulation Setup
114(1)
7.4.2 Trellis Depth as a Function of the Trellis Order and the Signal Amplitude
114(2)
7.4.3 Trellis Depth as a Function of the Signal Frequency
116(1)
7.4.4 Trellis Depth as a Function of the Loop-Filter Configuration
117(1)
7.4.5 Summary
118(1)
7.5 Functional Performance
119(12)
7.5.1 SNR, SINAD, THD and SFDR
119(5)
7.5.2 Converter Stability
124(4)
7.5.3 Noise Modulation
128(2)
7.5.4 Summary
130(1)
7.6 Implementation Aspects
131(4)
7.6.1 Required Computational Resources
131(1)
7.6.2 Look-Ahead Filter Unit
132(2)
7.6.3 Output Symbol Selection
134(1)
7.7 Conclusions
135(2)
8 Efficient Trellis Sigma-Delta Modulation
137(22)
8.1 Reducing the Number of Parallel Paths
137(3)
8.2 Algorithm
140(1)
8.3 Relation Between N and M
141(2)
8.4 Required History Length
143(2)
8.5 Functional Performance
145(8)
8.5.1 SNR, SINAD, THD and SFDR
145(4)
8.5.2 Converter Stability
149(1)
8.5.3 Noise Modulation
150(2)
8.5.4 Summary
152(1)
8.6 Implementation Aspects
153(3)
8.6.1 Selection Step
154(2)
8.7 Conclusions
156(3)
9 Pruned Tree Sigma-Delta Modulation
159(20)
9.1 Removing the Test for Uniqueness
159(2)
9.2 Algorithm
161(2)
9.2.1 Initialization Phase
162(1)
9.2.2 Operation Phase
162(1)
9.3 Required History Length
163(2)
9.4 Functional Performance
165(9)
9.4.1 SNR, SINAD, THD and SFDR
165(3)
9.4.2 Converter Stability
168(2)
9.4.3 Noise Modulation
170(2)
9.4.4 Summary
172(2)
9.5 Implementation Aspects
174(1)
9.6 Conclusions
175(4)
10 Pruned Tree Sigma-Delta Modulation for SA-CD
179(26)
10.1 Requirements of an SA-CD Modulator
179(2)
10.2 SA-CD Lossless Data Compression
181(3)
10.3 Dual Optimization
184(6)
10.3.1 Predictor Cost Function
185(2)
10.3.2 Combining the Cost Functions
187(1)
10.3.3 Spectral Shaping
188(2)
10.4 Algorithm
190(3)
10.5 Functional Performance
193(8)
10.5.1 Lossless Data Compression
193(1)
10.5.2 SNR, SINAD, THD and SFDR
194(2)
10.5.3 Converter Stability
196(1)
10.5.4 Noise Modulation
197(3)
10.5.5 Summary
200(1)
10.6 Implementation Aspects
201(1)
10.7 Conclusions
202(3)
11 Comparison of Look-Ahead SDM Techniques
205(20)
11.1 Alternative Look-Ahead Techniques
205(1)
11.2 Algorithm Comparison
206(3)
11.3 Functional Performance Comparison
209(12)
11.3.1 SNR, SINAD, THD and SFDR
209(4)
11.3.2 Converter Stability
213(3)
11.3.3 Noise Modulation
216(2)
11.3.4 Lossless Data Compression
218(2)
11.3.5 Summary
220(1)
11.4 Conclusions
221(4)
12 Maximum SNR Analysis
225(14)
12.1 Experiment 1
225(2)
12.2 Experiment 2
227(1)
12.3 Analysis
228(5)
12.3.1 Second Order Filter Stability
229(2)
12.3.2 High Order Filter Stability
231(2)
12.4 Obtaining the Maximum SNR
233(2)
12.5 Theoretical Maximum SNR
235(2)
12.6 Conclusions
237(2)
13 General Conclusions
239(2)
Appendix A FFT Calculations --- Coherent and Power Averaging 241(2)
Appendix B Description of the Used Sigma-Delta Modulators 243(2)
References 245