mohatta2015.pdf

Recommendations

Info

REFERENCES [Abd94] [Abe68] [Abe70] [Abr98] [Aff02] [Agg07] [And84] [Ari92] [Ari97] M. Abdulrahman, A. U. H. Sheikh, and D. D. Falconer, "Decision feedback equalization for CDMA in indoor wireless communications," IEEE J. Sel. Areas Commun., vol. 12, no. 4, pp. 698-706, May 1994. K. Abend, T. J. Harley, Jr., B. D. Fritchman, and C. Gumacos, "On optimum receivers for channels having memory," IEEE Trans. Inform. Theory, vol. IT-14, pp. 819-820, Nov. 1968. K. Abend and B. D. Fritchman, "Statistical detection for communication channels with intersymbol interference," Proc. IEEE, pp. 779-785, May 1970. E. Abreu, S. K. Mitra, and R. Marchesani, "Nonminimum phase channel equalization using noncausal filters," IEEE Trans. Sig. Proc., vol. 45, pp. 1-13, Jan. 1997 S. Affes, H. Hansen, and P. Mermelstein, "Interference subspace rejection: a framework for multiuser detection in wideband CDMA," IEEE J. Sel. Areas Commun., vol. 20, pp. 287-302, Feb. 2002. P. Aggarwal and X. Wang, "Multilevel sequential monte carlo algorithms for MIMO demodulation," IEEE Trans. Wireless Commun., vol. 6, pp. 750-758, Feb. 2007. J. B. Anderson and S. Mohan, "Sequential coding algorithms: a survey and cost analysis," IEEE Trans. Commun., vol. COM-32, pp. 169-176, Feb. 1984. S. Ariyavisitakul, "A decision feedback equalizer with time-reversal structure," IEEE J. Sel. Areas Commun., vol. 10, no. 3, pp. 599-613, Apr. 1992. S. Ariyavisitakul, N. R. Sollenberger, and L. J. Greenstein, "Tap-selectable decision-feedback equalization," IEEE Trans. Commun., vol. 45, pp. 1497-1500, Dec. 1997. Channel Equalization for Wireless Communications: From Concepts to Detailed 197 Mathematics, First Edition. Gregory E. Bottomley. © 2011 Institute of Electrical and Electronics Engineers, Inc. Published 2011 by John Wiley & Sons, Inc.
Page 2 and 3:
Channel Equalization for Wireless C
Page 4 and 5:
To my colleagues at Ericsson
Page 6 and 7:
CONTENTS List of Figures List of Ta
Page 8 and 9:
CONTENTS XI 4.2 4.3 4.4 4.5 4.6 4.1
Page 10 and 11:
CONTENTS XIII 8 Practical Considera
Page 12 and 13:
xvi LIST OF FIGURES 2.2 Matched fil
Page 14 and 15:
XviÜ LIST OF FIGURES 6.18 Scatter
Page 16 and 17:
XX Prologue Alice was nervous. Woul
Page 18 and 19:
XXÜ PREFACE is introduced as neede
Page 20 and 21:
ACRONYMS AC A/D ADC AMLD AMPS ASK A
Page 22 and 23:
ML MLD MLPD MLSD MLSE MRC MSE MSB O
Page 24 and 25:
2 INTRODUCTION Table 1.1 Possible m
Page 26 and 27:
4 INTRODUCTION s o S 1 8 2 S 3 S 0
Page 28 and 29:
6 INTRODUCTION A block diagram of t
Page 30 and 31:
8 INTRODUCTION Figure 1.7 QPSK. tra
Page 32 and 33:
10 INTRODUCTION phases (phase modul
Page 34 and 35:
12 INTRODUCTION rollo« 0.22 0.8 Ί
Page 36 and 37:
14 INTRODUCTION is the "channel" re
Page 38 and 39:
16 INTRODUCTION 1.4 MORE MATH In th
Page 40 and 41:
18 INTRODUCTION For K = 1 (order 0)
Page 42 and 43:
20 INTRODUCTION The K = 4 main bloc
Page 44 and 45:
22 INTRODUCTION A sample of the noi
Page 46 and 47:
24 INTRODUCTION The receiver may ha
Page 48 and 49:
26 INTRODUCTION 1.5.1 Reference sys
Page 50 and 51:
28 INTRODUCTION a) What most likely
Page 53 and 54:
CHAPTER 2 MATCHED FILTERING In this
Page 55 and 56:
MORE DETAILS 33 2.2 MORE DETAILS So
Page 57 and 58:
THE MATH 35 Now compare the output
Page 59 and 60:
THE MATH 37 The correlation in (2.2
Page 61 and 62:
THE MATH 39 correlation function f(
Page 63 and 64:
THE MATH 41 Thus, in the complex pl
Page 65 and 66:
THE MATH 43 to the medium response
Page 67 and 68:
THE MATH 45 We can interpret f(t) a
Page 69 and 70:
MORE MATH 47 10" 1 Odeg 90 deg X 18
Page 71 and 72:
MORE MATH 49 With despread-level Ra
Page 73 and 74:
MORE MATH 51 Figure 2.6 OFDM exampl
Page 75 and 76:
MORE MATH 53 2.4.3 MF in colored no
Page 77 and 78:
PROBLEMS 55 period) is examined in
Page 79 and 80:
CHAPTER 3 ZERO-FORCING DECISION FEE
Page 81 and 82:
MORE DETAILS 59 1/c r m —► H i
Page 83 and 84:
MORE DETAILS 61 where «i = m - (d/
Page 85 and 86:
MORE MATH 63 Because there is no IS
Page 87 and 88:
MORE MATH 65 In the later chapter o
Page 89 and 90:
PROBLEMS 67 b) What is the detected
Page 91 and 92:
CHAPTER 4 LINEAR EQUALIZATION With
Page 93 and 94:
THE IDEA 71 estimate of symbol s 2
Page 95 and 96:
THE IDEA 73 Notice that £2 (MSE) d
Page 97 and 98:
MORE DETAILS 75 The first term is t
Page 99 and 100:
MORE DETAILS 77 To obtain the unity
Page 101 and 102:
THE MATH 79 and SINR becomes w T h
Page 103 and 104:
THE MATH 81 To obtain the MMSE solu
Page 105 and 106:
THE MATH 83 where *m n = ν ^ ^ ^ '
Page 107 and 108:
THE MATH 85 power is much larger th
Page 109 and 110:
MORE MATH 87 IQ' 1 OC 111 ω 10 2 1
Page 111 and 112:
MORE MATH 89 values of h k m (f) fr
Page 113 and 114:
MORE MATH 91 where C(d(),d 0 ) . C(
Page 115 and 116:
AN EXAMPLE 93 between z and s. This
Page 117 and 118:
PROBLEMS 95 Another aspect of cocha
Page 119:
PROBLEMS 97 The math 4.11 Consider
Page 122 and 123:
100 MMSE AND ML DECISION FEEDBACK E
Page 124 and 125:
Page 126 and 127:
Page 128 and 129:
Page 130 and 131:
Page 132 and 133:
Page 134 and 135:
Page 137 and 138:
CHAPTER 6 MAXIMUM LIKELIHOOD SEQUEN
Page 139 and 140:
MORE DETAILS 117 r 2 Ht, r, fcl + f
Page 141 and 142:
MORE DETAILS 119 Figure 6.3 MLSD tr
Page 143 and 144:
THE MATH 121 legs of the journey is
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 195 and 196: CHAPTER 8 PRACTICAL CONSIDERATIONS
Page 197 and 198: MORE DETAILS 175 8.2 MORE DETAILS I
Page 199 and 200: MORE DETAILS 177 One extreme is to
Page 201 and 202: THE MATH 179 8.3.1 Time-invariant c
Page 203 and 204: THE MATH 181 With recursive channel
Page 205 and 206: MORE PRACTICAL ASPECTS 183 timing).
Page 207 and 208: THE LITERATURE 185 8.6 THE LITERATU
Page 209 and 210: PROBLEMS 187 a) Draw the new receiv
Page 211 and 212: APPENDIX A SIMULATION NOTES Perform
Page 213 and 214: FADING CHANNELS 191 where JA = A 2
Page 215 and 216: APPENDIX B NOTATION Channel Equaliz
Page 217: NOTATION 195 Variable Meaning p(t)
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
show all

mohatta2015.pdf

Create successful ePaper yourself

Delete template?

Save as template?