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CHAPTER 8 PRACTICAL CONSIDERATIONS So far, we've assumed we have a model of the received signal and that we know the parameters of that model. In practice, we don't know these parameters. Now what do we do? In this chapter we will briefly explore various answers to that question. It really takes another book to cover all the practical aspects of equalizer design and dig into the details. In this chapter, we will touch on some high level concepts and give some simple examples. Another consideration is which equalization approach to select. Should we always select the one with the best performance? What about complexity? Here we will give some guidance on how to make this choice. 8.1 THE IDEA So far, we have assumed we know some things about the received signal. Specifically, we assume we know 1. the channel response (channel coefficients c and d and delays 0 and 1 symbol periods), 2. the noise power (
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Channel Equalization for Wireless C
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To my colleagues at Ericsson
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CONTENTS List of Figures List of Ta
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CONTENTS XI 4.2 4.3 4.4 4.5 4.6 4.1
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CONTENTS XIII 8 Practical Considera
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xvi LIST OF FIGURES 2.2 Matched fil
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XviÜ LIST OF FIGURES 6.18 Scatter
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XX Prologue Alice was nervous. Woul
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XXÜ PREFACE is introduced as neede
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ACRONYMS AC A/D ADC AMLD AMPS ASK A
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ML MLD MLPD MLSD MLSE MRC MSE MSB O
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2 INTRODUCTION Table 1.1 Possible m
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4 INTRODUCTION s o S 1 8 2 S 3 S 0
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6 INTRODUCTION A block diagram of t
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8 INTRODUCTION Figure 1.7 QPSK. tra
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10 INTRODUCTION phases (phase modul
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12 INTRODUCTION rollo« 0.22 0.8 Ί
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14 INTRODUCTION is the "channel" re
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16 INTRODUCTION 1.4 MORE MATH In th
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18 INTRODUCTION For K = 1 (order 0)
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20 INTRODUCTION The K = 4 main bloc
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22 INTRODUCTION A sample of the noi
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24 INTRODUCTION The receiver may ha
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26 INTRODUCTION 1.5.1 Reference sys
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28 INTRODUCTION a) What most likely
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CHAPTER 2 MATCHED FILTERING In this
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MORE DETAILS 33 2.2 MORE DETAILS So
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THE MATH 35 Now compare the output
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THE MATH 37 The correlation in (2.2
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THE MATH 39 correlation function f(
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THE MATH 41 Thus, in the complex pl
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THE MATH 43 to the medium response
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THE MATH 45 We can interpret f(t) a
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MORE MATH 47 10" 1 Odeg 90 deg X 18
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MORE MATH 49 With despread-level Ra
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MORE MATH 51 Figure 2.6 OFDM exampl
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MORE MATH 53 2.4.3 MF in colored no
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PROBLEMS 55 period) is examined in
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CHAPTER 3 ZERO-FORCING DECISION FEE
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MORE DETAILS 59 1/c r m —► H i
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MORE DETAILS 61 where «i = m - (d/
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MORE MATH 63 Because there is no IS
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MORE MATH 65 In the later chapter o
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PROBLEMS 67 b) What is the detected
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CHAPTER 4 LINEAR EQUALIZATION With
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THE IDEA 71 estimate of symbol s 2
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THE IDEA 73 Notice that £2 (MSE) d
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MORE DETAILS 75 The first term is t
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MORE DETAILS 77 To obtain the unity
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THE MATH 79 and SINR becomes w T h
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THE MATH 81 To obtain the MMSE solu
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THE MATH 83 where *m n = ν ^ ^ ^ '
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THE MATH 85 power is much larger th
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MORE MATH 87 IQ' 1 OC 111 ω 10 2 1
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MORE MATH 89 values of h k m (f) fr
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MORE MATH 91 where C(d(),d 0 ) . C(
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AN EXAMPLE 93 between z and s. This
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PROBLEMS 95 Another aspect of cocha
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PROBLEMS 97 The math 4.11 Consider
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100 MMSE AND ML DECISION FEEDBACK E
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CHAPTER 6 MAXIMUM LIKELIHOOD SEQUEN
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MORE DETAILS 117 r 2 Ht, r, fcl + f
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MORE DETAILS 119 Figure 6.3 MLSD tr
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Page 145 and 146: THE MATH 123 Figure 6.8 MLSD trelli
Page 147 and 148: THE MATH 125 We would then identify
Page 149 and 150: THE MATH 127 Expanding the square,
Page 151 and 152: THE MATH 129 Consider the matched f
Page 153 and 154: THE MATH 131 6.3.5.1 M-algorithm Wi
Page 155 and 156: THE MATH 133 results, DFE and MLSD
Page 157 and 158: THE MATH 135 IQ" 1 oc LU CD 10 2 10
Page 159 and 160: THE MATH 137 sometimes inaccurate w
Page 161 and 162: MORE MATH 139 POWER CONTROL effecti
Page 163 and 164: MORE MATH 141 15 POWER CONTROL 10
Page 165 and 166: MORE MATH 143 6.4.3 More approximat
Page 167 and 168: THE LITERATURE 145 EDGE is an evolu
Page 169 and 170: PROBLEMS 147 the channel to minimum
Page 171: PROBLEMS 149 c) Suppose we know «o
Page 174 and 175: 152 ADVANCED TOPICS detecting the w
Page 176 and 177: 154 ADVANCED TOPICS Table 7.2 Examp
Page 178 and 179: 156 ADVANCED TOPICS Let's look at t
Page 180 and 181: 158 ADVANCED TOPICS Thus, for MAPSD
Page 182 and 183: 160 ADVANCED TOPICS Table 7.6 Examp
Page 184 and 185: 162 ADVANCED TOPICS If we assume no
Page 186 and 187: 164 ADVANCED TOPICS Now we can focu
Page 188 and 189: 166 ADVANCED TOPICS Notice we used
Page 190 and 191: 168 ADVANCED TOPICS to achieve spat
Page 192 and 193: 170 ADVANCED TOPICS c) What are the
Page 196 and 197: 174 PRACTICAL CONSIDERATIONS In pra
Page 198 and 199: 176 PRACTICAL CONSIDERATIONS adapti
Page 200 and 201: 178 PRACTICAL CONSIDERATIONS Figure
Page 202 and 203: 180 PRACTICAL CONSIDERATIONS 8.3.2
Page 204 and 205: 182 PRACTICAL CONSIDERATIONS When t
Page 206 and 207: 184 PRACTICAL CONSIDERATIONS from a
Page 208 and 209: 186 PRACTICAL CONSIDERATIONS a) Sup
Page 210 and 211: 188 PRACTICAL CONSIDERATIONS Epilog
Page 212 and 213: 190 SIMULATION NOTES etc., then the
Page 214 and 215: 192 SIMULATION NOTES and noise real
Page 216 and 217: 194 NOTATION Variable Meaning a lc
Page 219 and 220: REFERENCES [Abd94] [Abe68] [Abe70]
Page 221 and 222: REFERENCES 199 [Bau02] [Bel79] [Ben
Page 223 and 224: REFERENCES 201 [Cho04] [Chu96] [Cim
Page 225 and 226: REFERENCES 203 [For73] G. D. Forney
Page 227 and 228: REFERENCES 205 [Hoe99] P. Hoeher an
Page 229 and 230: REFERENCES 207 Signal Processing
Page 231 and 232: REFERENCES 209 [Mon84] [Mud04] [Nag
Page 233 and 234: REFERENCES 211 [San96] [Say98] [Say
Page 235 and 236: REFERENCES 213 [Vac81] G. M. Vachul
Page 237: REFERENCES 215 [Xie90b] [Xio90] [Yo
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