| Preface |
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xxv | |
| Acknowledgements |
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xxvii | |
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1 Elements of signal theory |
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1 | (1) |
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1.1 Continuous-time linear systems |
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1 | (1) |
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1.2 Discrete-time linear systems |
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2 | (12) |
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Discrete Fourier transform |
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7 | (1) |
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7 | (1) |
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Circular and linear convolution via DFT |
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8 | (2) |
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Convolution by the overlap-save method |
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10 | (1) |
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11 | (3) |
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14 | (4) |
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17 | (1) |
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Heaviside conditions for the absence of signal distortion |
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17 | (1) |
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1.4 Passband signals and systems |
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18 | (11) |
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18 | (3) |
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Relation between a signal and its complex representation |
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21 | (5) |
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Baseband equivalent of a transformation |
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26 | (2) |
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Envelope and instantaneous phase and frequency |
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28 | (1) |
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1.5 Second-order analysis of random processes |
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29 | (14) |
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29 | (1) |
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Properties of the autocorrelation function |
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30 | (1) |
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1.5.2 Power spectral density |
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30 | (1) |
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Spectral lines in the PSD |
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30 | (1) |
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Cross power spectral density |
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31 | (1) |
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32 | (1) |
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32 | (1) |
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1.5.3 PSD of discrete-time random processes |
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32 | (1) |
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Spectral lines in the PSD |
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33 | (1) |
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34 | (1) |
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Minimum-phase spectral factorization |
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35 | (1) |
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1.5.4 PSD of passband processes |
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36 | (1) |
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PSD of in-phase and quadrature components |
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36 | (2) |
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Cyclostationary processes |
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38 | (5) |
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1.6 The autocorrelation matrix |
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43 | (3) |
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1.7 Examples of random processes |
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46 | (6) |
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52 | (3) |
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53 | (2) |
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1.9 Ergodic random processes |
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55 | (10) |
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1.9.1 Mean value estimators |
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57 | (1) |
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58 | (1) |
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59 | (1) |
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59 | (1) |
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1.9.2 Correlation estimators |
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60 | (1) |
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60 | (1) |
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60 | (1) |
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1.9.3 Power spectral density estimators |
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61 | (1) |
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Periodogram or instantaneous spectrum |
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61 | (1) |
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62 | (1) |
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Blackman and Tukey correlogram |
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63 | (1) |
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Windowing and window closing |
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63 | (2) |
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1.10 Parametric models of random processes |
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65 | (13) |
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65 | (2) |
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67 | (1) |
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67 | (2) |
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Spectral factorization of AR models |
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69 | (1) |
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70 | (1) |
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Relation between ARMA, MA, and AR models |
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70 | (2) |
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1.10.1 Autocorrelation of AR processes |
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72 | (2) |
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1.10.2 Spectral estimation of an AR process |
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74 | (1) |
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75 | (2) |
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AR model of sinusoidal processes |
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77 | (1) |
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1.11 Guide to the bibliography |
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78 | (1) |
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78 | (1) |
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Appendix 1.A Multirate systems |
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79 | (1) |
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79 | (2) |
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81 | (2) |
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83 | (1) |
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84 | (2) |
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1.A.5 Interpolator filter |
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86 | (2) |
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88 | (2) |
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90 | (1) |
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90 | (1) |
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91 | (1) |
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1.A.8 The noble identities |
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91 | (1) |
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1.A.9 The polyphase representation |
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92 | (6) |
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Efficient implementations |
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93 | (5) |
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Appendix 1B Generation of a complex Gaussian noise |
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98 | (1) |
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Appendix 1C Pseudo-noise sequences |
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99 | (43) |
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99 | (2) |
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101 | (1) |
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102 | (3) |
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105 | (1) |
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105 | (1) |
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106 | (1) |
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107 | (2) |
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The principle of orthogonality |
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109 | (1) |
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Expression of the minimum mean-square error |
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110 | (1) |
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Characterization of the cost function surface |
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110 | (1) |
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The Wiener filter in the z-domain |
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111 | (3) |
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114 | (4) |
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115 | (660) |
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Optimum predictor coefficients |
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115 | (1) |
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Forward prediction error filter |
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116 | (1) |
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Relation between linear prediction and AR models |
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117 | (1) |
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First - and second-order solutions |
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117 | |
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2.3 The least squares method |
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118 | (1) |
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119 | (1) |
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119 | (1) |
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120 | (1) |
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Determination of the optimum filter coefficients |
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120 | (1) |
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2.3.1 The principle of orthogonality |
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121 | (1) |
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121 | (1) |
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The normal equation using the data matrix |
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122 | (1) |
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Geometric interpretation: the projection operator |
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122 | (3) |
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2.3.2 Solutions to the LS problem |
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125 | (1) |
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Singular value decomposition |
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125 | (1) |
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125 | (1) |
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2.4 The estimation problem |
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126 | (1) |
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Estimation of a random variable |
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126 | (1) |
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127 | (1) |
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Extension to multiple observations |
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127 | (4) |
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Linear MMSE estimation of a random variable |
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129 | (1) |
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Linear MMSE estimation of a random vector |
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129 | (2) |
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2.4.1 The Cramer-Rao lower bound |
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131 | (1) |
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Extension to vector parameter |
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132 | (2) |
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2.5 Examples of application |
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134 | (1) |
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2.5.1 Identification of a linear discrete-time system |
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134 | (1) |
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2.5.2 Identification of a continuous-time system |
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135 | (3) |
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2.5.3 Cancellation of an interfering signal |
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138 | (1) |
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2.5.4 Cancellation of a sinusoidal interferer with known frequency |
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139 | (1) |
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2.5.5 Echo cancellation in digital subscriber loops |
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140 | (1) |
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2.5.6 Cancellation of a periodic interferer |
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141 | (1) |
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142 | (1) |
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Appendix 2 A The Levinson-Durbin algorithm |
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142 | (2) |
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144 | (1) |
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The Delsarte-Genin algorithm |
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145 | (2) |
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3 Adaptive transversal filters |
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147 | (1) |
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3.1 The MSE design criterion |
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148 | (29) |
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3.1.1 The steepest descent or gradient algorithm |
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148 | (1) |
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149 | (1) |
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Conditions for convergence |
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150 | (1) |
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151 | (1) |
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Transient behaviour of the MSE |
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152 | (1) |
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3.1.2 The least mean square algorithm |
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153 | (1) |
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154 | (1) |
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155 | (1) |
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Conditions for convergence |
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155 | (1) |
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3.1.3 Convergence analysis of the LMS algorithm |
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156 | (1) |
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157 | (1) |
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Convergence in the mean-square sense: real scalar case |
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157 | (2) |
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Convergence in the mean-square sense: general case |
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159 | (2) |
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161 | (1) |
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162 | (1) |
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163 | (1) |
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3.1.4 Other versions of the LMS algorithm |
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163 | (1) |
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164 | (1) |
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164 | (1) |
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164 | (1) |
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165 | (1) |
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3.1.5 Example of application: the predictor |
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166 | (11) |
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3.2 The recursive least squares algorithm |
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177 | (1) |
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172 | (3) |
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173 | (1) |
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174 | (1) |
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Recursive form of the minimum cost function |
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175 | (1) |
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176 | (1) |
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176 | (1) |
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Example of application: the predictor |
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177 | (1) |
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3.3 Fast recursive algorithms |
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177 | (1) |
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3.3.1 Comparison of the various algorithms |
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177 | (1) |
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3.4 Examples of application |
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178 | (5) |
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3.4.1 Identification of a linear discrete-time system |
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178 | (1) |
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179 | (8) |
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3.4.2 Cancellation of a sinusoidal interferer with known frequency |
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187 | (1) |
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187 | |
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183 | (43) |
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183 | (39) |
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4.1.1 Propagation and used frequencies in radio transmission |
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183 | (1) |
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Basic propagation mechanisms |
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184 | (1) |
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184 | (1) |
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4.1.2 Analog front-end architectures |
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185 | (1) |
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185 | (1) |
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Conventional superheterodyne receiver |
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186 | (1) |
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Alternative architectures |
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187 | (1) |
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Direct conversion receiver |
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187 | (1) |
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Single conversion to low-IF |
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188 | (1) |
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Double conversion and wideband IF |
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188 | (1) |
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4.1.3 General channel model |
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189 | (1) |
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189 | (2) |
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191 | (1) |
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191 | (1) |
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191 | (2) |
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4.1.4 Narrowband radio channel model |
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193 | (2) |
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Equivalent circuit at the receiver |
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195 | (1) |
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196 | (1) |
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Path loss as a function of distance |
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197 | (3) |
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4.1.5 Fading effects in propagation models |
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200 | (1) |
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Macroscopic fading or shadowing |
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200 | (7) |
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207 | |
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202 | (2) |
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4.1.7 Wideband channel model |
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204 | (1) |
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Multipath channel parameters |
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205 | (1) |
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Statistical description of fading channels |
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206 | (2) |
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208 | (1) |
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208 | (1) |
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209 | (1) |
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210 | (1) |
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211 | (1) |
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211 | (1) |
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211 | (1) |
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212 | (1) |
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212 | (3) |
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4.1.9 Discrete-time model for fading channels |
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215 | (1) |
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Generation of a process with a pre-assigned spectrum |
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215 | (2) |
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4.1.10 Discrete-space model of shadowing |
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216 | (2) |
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4.1.11 Multiantenna systems |
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218 | (1) |
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218 | (1) |
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219 | (1) |
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Small number of scatterers |
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220 | (1) |
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Large number of scatterers |
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220 | (2) |
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222 | (1) |
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222 | (4) |
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222 | (1) |
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222 | (1) |
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222 | (2) |
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224 | (1) |
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224 | (1) |
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225 | (1) |
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Appendix 4.A Discrete-time NB model for mm Wave channels |
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226 | (51) |
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4.A.1 Angular domain representation |
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226 | (3) |
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229 | (20) |
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229 | (1) |
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5.2 Characterization of VQ |
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230 | (3) |
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Parameters determining VQ performance |
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231 | (1) |
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Comparison between VQ and scalar quantization |
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232 | (1) |
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233 | (2) |
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Generalized Lloyd algorithm |
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233 | (2) |
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5.4 The Linde, Buzo, and Gray algorithm |
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235 | (4) |
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Choice of the initial codebook |
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236 | (1) |
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236 | (2) |
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Selection of the training sequence |
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238 | (1) |
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239 | (1) |
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239 | (3) |
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239 | (1) |
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240 | (1) |
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240 | (2) |
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5.6 VQ of channel state information |
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242 | (2) |
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MISO channel quantization |
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242 | (2) |
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Channel feedback with feedforward information |
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244 | (1) |
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5.7 Principal component analysis |
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244 | (5) |
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5.7.1 PCA and &-means clustering |
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246 | (2) |
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248 | (1) |
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6 Digital transmission model and channel capacity |
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249 | (28) |
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6.1 Digital transmission model |
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249 | (4) |
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253 | (7) |
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253 | (1) |
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254 | (1) |
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254 | (2) |
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256 | (1) |
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LLRs associated to bits of BMAP |
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256 | (2) |
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258 | (2) |
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6.2.3 Receiver strategies |
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260 | (1) |
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6.3 Relevant parameters of the digital transmission model |
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260 | (2) |
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Relations among parameters |
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261 | (1) |
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262 | (3) |
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265 | (5) |
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6.5.1 Discrete-time AWGN channel |
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266 | (1) |
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6.5.2 SISO narrowband AWGN channel |
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266 | (1) |
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267 | (1) |
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6.5.3 SISO dispersive AGN channel |
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267 | (2) |
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6.5.4 MIMO discrete-time NB AWGN channel |
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269 | (1) |
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270 | (1) |
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270 | (1) |
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6.6 Achievable rates of modulations in AWGN channels |
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270 | (7) |
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6.6.1 Rate as a function of the SNR per dimension |
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271 | (1) |
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6.6.2 Coding strategies depending on the signal-to-noise ratio |
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272 | (2) |
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274 | (1) |
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6.6.3 Achievable rate of an AWGN channel using PAM |
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275 | (1) |
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276 | (1) |
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Appendix 6 A Gray labelling |
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277 | (112) |
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Appendix 6.B The Gaussian distribution and Marcum functions |
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278 | (3) |
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278 | (1) |
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279 | (2) |
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7 Single-carrier modulation |
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281 | (108) |
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281 | (13) |
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7.1.1 Baseband digital transmission (PAM) |
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281 | (1) |
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281 | (2) |
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283 | (1) |
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283 | (1) |
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284 | (1) |
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7.1.2 Passband digital transmission (QAM) |
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285 | (1) |
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285 | (1) |
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286 | (1) |
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Three equivalent representations of the modulator |
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287 | (1) |
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288 | (1) |
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7.1.3 Baseband equivalent model of a QAM system |
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288 | (1) |
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288 | (3) |
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7.1.4 Characterization of system elements |
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291 | (1) |
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291 | (6) |
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291 | (2) |
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293 | (1) |
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7.2 Intersymbol interference |
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294 | (8) |
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Discrete-time equivalent system |
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294 | (1) |
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295 | (3) |
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298 | (4) |
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302 | (2) |
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302 | (1) |
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Symbol error probability in the absence of ISI |
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303 | (1) |
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303 | (1) |
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304 | (36) |
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7.4.1 Zero-forcing equalizer |
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304 | (1) |
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305 | (1) |
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Optimum receiver in the presence of noise and ISI |
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305 | (1) |
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Alternative derivation of the IIR equalizer |
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306 | (4) |
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Signal-to-noise ratio at detector |
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310 | (1) |
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7.4.3 LE with a finite number of coefficients |
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310 | (261) |
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311 | (4) |
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Fractionally spaced equalizer |
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315 | (1) |
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7.4.4 Decision feedback equalizer |
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315 | (3) |
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Design of a DFE with a finite number of coefficients |
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318 | (2) |
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Design of a fractionally spaced DFE |
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320 | (2) |
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Signal-to-noise ratio at the decision point |
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322 | (1) |
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322 | (1) |
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7.4.5 Frequency domain equalization |
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323 | (1) |
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DFE with data frame using a unique word |
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323 | (3) |
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326 | (1) |
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7.4.7 DFE-ZF with IIR filters |
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327 | (4) |
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DFE-ZF as noise predictor |
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331 | (1) |
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DFE as ISI and noise predictor |
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331 | (2) |
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7.4.8 Benchmark performance of LE-ZF and DFE-ZF |
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333 | (1) |
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333 | (1) |
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Performance for two channel models |
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334 | (1) |
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7.4.9 Passband equalizers |
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335 | (1) |
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Passband receiver structure |
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335 | (2) |
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Optimization of equalizer coefficients and carrier phase offset |
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337 | (1) |
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338 | (2) |
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7.5 Optimum methods for data detection |
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340 | (30) |
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Maximum a posteriori probability (MAP) criterion |
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341 | (1) |
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7.5.1 Maximum-likelihood sequence detection |
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341 | (1) |
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Lower bound to error probability using MLSD |
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342 | (1) |
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343 | (3) |
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Computational complexity of the VA |
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346 | (1) |
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7.5.2 Maximum a posteriori probability detector |
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347 | (1) |
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Statistical description of a sequential machine |
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347 | (1) |
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The forward-backward algorithm |
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348 | (3) |
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351 | (1) |
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The log likelihood function and the Max-Log-MAP criterion |
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352 | (1) |
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LLRs associated to bits of BMAP |
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353 | (1) |
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Relation between Max-Log-MAP and Log-MAP |
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354 | (1) |
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354 | (2) |
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7.5.4 The Ungerboeck's formulation of MLSD |
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356 | (2) |
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7.5.5 Error probability achieved by MLSD |
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358 | (3) |
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Computation of the minimum distance |
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361 | (4) |
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7.5.6 The reduced-state sequence detection |
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365 | (1) |
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365 | (2) |
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367 | (2) |
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Further simplification: DFSE |
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369 | (1) |
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7.6 Numerical results obtained by simulations |
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370 | (3) |
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QPSK over a minimum-phase channel |
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|
370 | (1) |
|
QPSK over a non-minimum phase channel |
|
|
370 | (2) |
|
8-PSK over a minimum phase channel |
|
|
372 | (1) |
|
8-PSK over a non-minimum phase channel |
|
|
372 | (1) |
|
7.7 Precoding for dispersive channels |
|
|
373 | (5) |
|
7.7.1 Tornlinson-Harashima precoding |
|
|
374 | (2) |
|
|
|
376 | (2) |
|
|
|
378 | (8) |
|
7.8.1 The correlation method |
|
|
378 | (1) |
|
|
|
379 | (1) |
|
Formulation using the data matrix |
|
|
380 | (1) |
|
7.8.3 Signal-to-estimation error ratio |
|
|
380 | (1) |
|
Computation of the signal-to-estimation error ratio |
|
|
381 | (3) |
|
On the selection of the channel length |
|
|
384 | (1) |
|
7.8.4 Channel estimation for multirate systems |
|
|
384 | (1) |
|
|
|
385 | (1) |
|
7.9 Faster-than-Nyquist Signalling |
|
|
386 | (3) |
|
|
|
387 | (2) |
|
Appendix 7.A Simulation of a QAM system |
|
|
389 | (4) |
|
Appendix 7.B Description of a finite-state machine |
|
|
393 | (1) |
|
Appendix 7.C Line codes for PAM systems |
|
|
394 | (117) |
|
|
|
394 | (5) |
|
Non-return-to-zero format |
|
|
395 | (1) |
|
|
|
396 | (1) |
|
|
|
397 | (1) |
|
Delay modulation or Miller code |
|
|
398 | (1) |
|
|
|
398 | (1) |
|
|
|
398 | (1) |
|
7.C.2 Partial response systems |
|
|
399 | (11) |
|
The choice of the PR polynomial |
|
|
401 | (3) |
|
Symbol detection and error probability |
|
|
404 | (2) |
|
|
|
406 | (1) |
|
Error probability with precoding |
|
|
407 | (1) |
|
Alternative interpretation of PR systems |
|
|
408 | (2) |
|
7.D Implementation of a QAM transmitter |
|
|
410 | (3) |
|
8 Multicarrier modulation |
|
|
413 | (34) |
|
|
|
413 | (1) |
|
8.2 Orthogonality conditions |
|
|
414 | (2) |
|
|
|
415 | (1) |
|
|
|
415 | (1) |
|
|
|
415 | (1) |
|
8.3 Efficient implementation of MC systems |
|
|
416 | (6) |
|
MC implementation employing matched filters |
|
|
416 | (2) |
|
Orthogonality conditions in terms of the polyphase components |
|
|
418 | (1) |
|
MC implementation employing a prototype filter |
|
|
419 | (3) |
|
8.4 Non-critically sampled filter banks |
|
|
422 | (4) |
|
8.5 Examples of MC systems |
|
|
426 | (3) |
|
|
|
426 | (1) |
|
|
|
427 | (2) |
|
8.6 Analog signal processing requirements in MC systems |
|
|
429 | (3) |
|
8.6.1 Analog filter requirements |
|
|
429 | (1) |
|
Interpolator filter and virtual subchannels |
|
|
429 | (1) |
|
|
|
430 | (1) |
|
8.6.2 Power amplifier requirements |
|
|
431 | (1) |
|
|
|
432 | (5) |
|
|
|
432 | (2) |
|
|
|
434 | (1) |
|
Per-subchannel fractionally spaced equalization |
|
|
434 | (1) |
|
Per-subchannel T-spaced equalization |
|
|
435 | (1) |
|
Alternative per-subchannel T-spaced equalization |
|
|
436 | (1) |
|
8.8 Orthogonal time frequency space modulation |
|
|
437 | (1) |
|
|
|
437 | (1) |
|
8.9 Channel estimation in OFDM |
|
|
437 | (5) |
|
Instantaneous estimate or LS method |
|
|
438 | (2) |
|
|
|
440 | (1) |
|
The LS estimate with truncated impulse response |
|
|
440 | (1) |
|
8.9.1 Channel estimate and pilot symbols |
|
|
441 | (1) |
|
8.10 Multiuser access schemes |
|
|
442 | (2) |
|
|
|
442 | (1) |
|
8.10.2 SC-FDMA or DFT-spread OFDM |
|
|
443 | (1) |
|
8.11 Comparison between MC and SC systems |
|
|
444 | (1) |
|
|
|
445 | (2) |
|
|
|
446 | (1) |
|
9 Transmission over multiple input multiple output channels |
|
|
447 | (36) |
|
|
|
447 | (5) |
|
Spatial multiplexing and spatial diversity |
|
|
451 | (1) |
|
Interference in MIMO channels |
|
|
452 | (1) |
|
9.2 CSI only at the receiver |
|
|
452 | (11) |
|
|
|
452 | (3) |
|
Equalization and diversity |
|
|
455 | (1) |
|
|
|
455 | (1) |
|
|
|
456 | (1) |
|
|
|
456 | (1) |
|
9.2.3 MIMO non-linear detection and decoding |
|
|
457 | (1) |
|
|
|
457 | (1) |
|
|
|
458 | (1) |
|
|
|
459 | (1) |
|
|
|
459 | (2) |
|
|
|
461 | (1) |
|
9.2.5 MIMO channel estimation |
|
|
461 | (1) |
|
|
|
462 | (1) |
|
|
|
463 | (1) |
|
9.3 CSI only at the transmitter |
|
|
463 | (6) |
|
9.3.1 MISO linear precoding |
|
|
463 | (1) |
|
|
|
464 | (1) |
|
9.3.2 MIMO linear precoding |
|
|
465 | (1) |
|
|
|
465 | (1) |
|
9.3.3 MIMO non-linear precoding |
|
|
466 | (1) |
|
|
|
467 | (1) |
|
|
|
468 | (1) |
|
9.3.4 Channel estimation for CSIT |
|
|
469 | (1) |
|
9.4 CSI at both the transmitter and the receiver |
|
|
469 | (1) |
|
|
|
470 | (2) |
|
Hybrid beamforming and angular domain representation |
|
|
472 | (1) |
|
9.6 Multiuser MIMO: broadcast channel |
|
|
472 | (4) |
|
CSI only at the receivers |
|
|
473 | (1) |
|
CSI only at the transmitter |
|
|
473 | (1) |
|
9.6.1 CSI at both the transmitter and the receivers |
|
|
473 | (1) |
|
|
|
473 | (1) |
|
|
|
474 | (1) |
|
Joint spatial division and multiplexing |
|
|
475 | (1) |
|
9.6.2 Broadcast channel estimation |
|
|
476 | (1) |
|
9.7 Multiuser MIMO: multiple-access channel |
|
|
476 | (2) |
|
CSI only at the transmitters |
|
|
477 | (1) |
|
|
|
477 | (1) |
|
9.7.1 CSI at both the transmitters and the receiver |
|
|
477 | (1) |
|
|
|
477 | (1) |
|
9.7.2 Multiple-access channel estimation |
|
|
478 | (1) |
|
|
|
478 | (5) |
|
|
|
478 | (1) |
|
9.8.2 Multiuser channel orthogonality |
|
|
479 | (1) |
|
|
|
479 | (4) |
|
10 Spread-spectrum systems |
|
|
483 | (28) |
|
10.1 Spread-spectrum techniques |
|
|
483 | (10) |
|
10.1.1 Direct sequence systems |
|
|
483 | (7) |
|
Classification of CDMA systems |
|
|
490 | (1) |
|
|
|
490 | (1) |
|
10.1.2 Frequency hopping systems |
|
|
491 | (1) |
|
Classification of FH systems |
|
|
491 | (2) |
|
10.2 Applications of spread-spectrum systems |
|
|
493 | (3) |
|
|
|
494 | (2) |
|
|
|
496 | (1) |
|
10.2.3 Interference rejection |
|
|
496 | (1) |
|
10.3 Chip matched filter and rake receiver |
|
|
496 | (4) |
|
Number of resolvable rays in a multipath channel |
|
|
497 | (1) |
|
|
|
498 | (2) |
|
|
|
500 | (2) |
|
Detection strategies for multiple-access systems |
|
|
502 | (1) |
|
10.5 Single-user detection |
|
|
502 | (2) |
|
|
|
502 | (1) |
|
|
|
503 | (1) |
|
|
|
504 | (5) |
|
|
|
504 | (2) |
|
10.6.2 Interference cancellation detector |
|
|
506 | (1) |
|
Successive interference cancellation |
|
|
506 | (1) |
|
Parallel interference cancellation |
|
|
507 | (1) |
|
10.6.3 ML multiuser detector |
|
|
508 | (1) |
|
|
|
508 | (1) |
|
|
|
508 | (1) |
|
10.7 Multicarrier CDMA systems |
|
|
509 | (2) |
|
|
|
510 | (1) |
|
Appendix 10 A Walsh Codes |
|
|
511 | |
|
|
|
515 | |
|
|
|
516 | (1) |
|
|
|
517 | (59) |
|
11.2.1 Theory of binary codes with group structure |
|
|
518 | (1) |
|
|
|
518 | (2) |
|
|
|
520 | (2) |
|
|
|
522 | (1) |
|
Decoding of binary parity check codes |
|
|
523 | (1) |
|
|
|
523 | (1) |
|
Two conceptually simple decoding methods |
|
|
524 | (1) |
|
|
|
525 | (2) |
|
11.2.2 Fundamentals of algebra |
|
|
527 | (1) |
|
|
|
528 | (2) |
|
Polynomials with coefficients from a field |
|
|
530 | (1) |
|
Modular arithmetic for polynomials |
|
|
531 | (3) |
|
Devices to sum and multiply elements in a finite field |
|
|
534 | (1) |
|
|
|
535 | (3) |
|
|
|
538 | (3) |
|
|
|
541 | (1) |
|
Methods to determine the minimum function |
|
|
542 | (2) |
|
Properties of the minimum function |
|
|
544 | (1) |
|
|
|
545 | (1) |
|
The algebra of cyclic codes |
|
|
545 | (1) |
|
Properties of cyclic codes |
|
|
546 | (5) |
|
Encoding by a shift register of length r |
|
|
551 | (1) |
|
Encoding by a shift register of length k |
|
|
552 | (1) |
|
Hard decoding of cyclic codes |
|
|
552 | (2) |
|
|
|
554 | (2) |
|
|
|
556 | (1) |
|
11.2.4 Simplex cyclic codes |
|
|
556 | (1) |
|
|
|
557 | (1) |
|
|
|
558 | (1) |
|
|
|
558 | (1) |
|
An alternative method to specify the code polynomials |
|
|
558 | (2) |
|
Bose-Chaudhuri-Hocquenhem codes |
|
|
560 | (2) |
|
|
|
562 | (2) |
|
|
|
564 | (2) |
|
|
|
566 | (2) |
|
Efficient decoding of BCH codes |
|
|
568 | (7) |
|
11.2.6 Performance of block codes |
|
|
575 | (1) |
|
|
|
576 | (17) |
|
11.3.1 General description of convolutional codes |
|
|
579 | (2) |
|
|
|
581 | (1) |
|
|
|
581 | (1) |
|
|
|
582 | (3) |
|
Catastrophic error propagation |
|
|
585 | (1) |
|
11.3.2 Decoding of convolutional codes |
|
|
586 | (1) |
|
|
|
587 | (1) |
|
|
|
587 | (1) |
|
Decoding by the Viterbi algorithm |
|
|
588 | (1) |
|
Decoding by the forward-backward algorithm |
|
|
589 | (1) |
|
|
|
590 | (2) |
|
11.3.3 Performance of convolutional codes |
|
|
592 | (1) |
|
|
|
593 | (1) |
|
|
|
593 | (4) |
|
The soft-output Viterbi algorithm |
|
|
593 | (4) |
|
|
|
597 | (80) |
|
|
|
597 | (3) |
|
The basic principle of iterative decoding |
|
|
600 | (7) |
|
|
|
607 | (1) |
|
|
|
608 | (62) |
|
|
|
670 | (7) |
|
11.7 Iterative detection and decoding |
|
|
677 | |
|
11.8 Low-density parity check codes |
|
|
614 | (13) |
|
11.8.1 Representation of LDPC codes |
|
|
614 | (1) |
|
|
|
614 | (1) |
|
|
|
615 | (1) |
|
|
|
616 | (1) |
|
|
|
616 | (1) |
|
|
|
617 | (1) |
|
|
|
617 | (2) |
|
The sum-product algorithm decoder |
|
|
619 | (3) |
|
|
|
622 | (1) |
|
The LLR-SPA or log-domain SPA decoder |
|
|
623 | (2) |
|
|
|
625 | (1) |
|
Other decoding algorithms |
|
|
625 | (1) |
|
11.8.4 Example of application |
|
|
625 | (1) |
|
Performance and coding gain |
|
|
625 | (2) |
|
11.8.5 Comparison with turbo codes |
|
|
627 | (1) |
|
|
|
627 | (21) |
|
|
|
628 | (2) |
|
|
|
630 | (1) |
|
LLRs associated to code bits |
|
|
631 | (1) |
|
|
|
631 | (2) |
|
11.9.3 Decoding algorithms |
|
|
633 | (1) |
|
Successive cancellation decoding - the principle |
|
|
634 | (1) |
|
Successive cancellation decoding - the algorithm |
|
|
635 | (3) |
|
Successive cancellation list decoding |
|
|
638 | (1) |
|
Other decoding algorithms |
|
|
639 | (1) |
|
|
|
640 | (1) |
|
|
|
640 | (1) |
|
Design based on density evolution |
|
|
641 | (2) |
|
|
|
643 | (1) |
|
11.9.5 Puncturing and shortening |
|
|
644 | (1) |
|
|
|
644 | (1) |
|
|
|
645 | (2) |
|
|
|
647 | (1) |
|
|
|
647 | (1) |
|
11.10 Milestones in channel coding |
|
|
648 | |
|
|
|
649 | |
|
|
|
11 | (773) |
|
A Non-binary parity check codes |
|
|
652 | (7) |
|
|
|
653 | (1) |
|
|
|
654 | (1) |
|
|
|
655 | (1) |
|
Decoding of non-binary parity check codes |
|
|
656 | (1) |
|
|
|
656 | (1) |
|
Two conceptually simple decoding methods |
|
|
656 | (1) |
|
|
|
657 | (2) |
|
12 Trellis coded modulation |
|
|
659 | (28) |
|
12.1 Linear TCM for one- and two-dimensional signal sets |
|
|
660 | (19) |
|
12.1.1 Fundamental elements |
|
|
660 | (1) |
|
|
|
661 | (1) |
|
|
|
662 | (2) |
|
|
|
664 | (2) |
|
|
|
666 | (5) |
|
12.1.4 Assignment of symbols to the transitions in the trellis |
|
|
671 | (4) |
|
12.1.5 General structure of the encoder/bit-mapper |
|
|
675 | (2) |
|
|
|
677 | (2) |
|
12.2 Multidimensional TCM |
|
|
679 | (5) |
|
|
|
680 | (2) |
|
|
|
682 | (2) |
|
12.3 Rotationally invariant TCM schemes |
|
|
684 | (3) |
|
|
|
685 | (2) |
|
13 Techniques to achieve capacity |
|
|
687 | (18) |
|
13.1 Capacity achieving solutions for multicarrier systems |
|
|
687 | (11) |
|
13.1.1 Achievable bit rate of OFDM |
|
|
687 | (1) |
|
13.1.2 Waterfilling solution |
|
|
688 | (1) |
|
|
|
689 | (1) |
|
13.1.3 Achievable rate under practical constraints |
|
|
689 | (1) |
|
Effective SNR and system margin in MC systems |
|
|
690 | (1) |
|
Uniform power allocation and minimum rate per subchannel |
|
|
690 | (1) |
|
13.1.4 The bit and power loading problem revisited |
|
|
691 | (1) |
|
|
|
692 | (1) |
|
Some simplifying assumptions |
|
|
692 | (1) |
|
|
|
693 | (1) |
|
The Hughes-Hartogs algorithm |
|
|
694 | (1) |
|
The Krongold-Ramchandran-Jones algorithm |
|
|
694 | (2) |
|
The Chow-Cioffi-Bingham algorithm |
|
|
696 | (2) |
|
|
|
698 | (1) |
|
13.2 Capacity achieving solutions for single carrier systems |
|
|
698 | (7) |
|
|
|
702 | (1) |
|
|
|
703 | (2) |
|
|
|
705 | (1) |
|
14.1 The problem of synchronization for QAM systems |
|
|
705 | (2) |
|
14.2 The phase-locked loop |
|
|
707 | (1) |
|
14.2.1 PLL baseband model |
|
|
708 | (1) |
|
|
|
709 | (2) |
|
14.2.2 Analysis of the PLL in the presence of additive noise |
|
|
711 | (1) |
|
Noise analysis using the linearity assumption |
|
|
711 | (2) |
|
14.2.3 Analysis of a second-order PLL |
|
|
713 | (3) |
|
|
|
716 | (4) |
|
|
|
716 | (3) |
|
|
|
719 | (1) |
|
14.4 The optimum receiver |
|
|
720 | (5) |
|
|
|
721 | (4) |
|
|
|
725 | (1) |
|
14.5 Algorithms for timing and carrier phase recovery |
|
|
725 | (15) |
|
|
|
726 | (1) |
|
Assumption of slow time varying channel |
|
|
726 | (1) |
|
14.5.2 Taxonomy of algorithms using the ML criterion |
|
|
726 | (1) |
|
|
|
727 | (1) |
|
|
|
728 | (1) |
|
|
|
729 | (1) |
|
|
|
729 | (3) |
|
NDA synchronization via spectral estimation |
|
|
732 | (1) |
|
Data aided and data directed |
|
|
733 | (2) |
|
Data and phase directed with feedback: differentiator scheme |
|
|
735 | (1) |
|
Data and phase directed with feedback: Mueller and Muller scheme |
|
|
735 | (3) |
|
Non-data aided with feedback |
|
|
738 | (1) |
|
|
|
738 | (1) |
|
|
|
738 | (1) |
|
Non-data aided for M-PSK signals |
|
|
738 | (1) |
|
Data and timing directed with feedback |
|
|
739 | (1) |
|
14.6 Algorithms for carrier frequency recovery |
|
|
740 | (4) |
|
14.6.1 Frequency offset estimators |
|
|
741 | (1) |
|
|
|
741 | (1) |
|
Non-data aided and timing independent with feedback |
|
|
742 | (1) |
|
Non-data aided and timing directed with feedback |
|
|
743 | (1) |
|
14.6.2 Estimators operating at the modulation rate |
|
|
743 | (1) |
|
Data aided and data directed |
|
|
744 | (1) |
|
|
|
744 | (1) |
|
14.7 Second-order digital PLL |
|
|
744 | (1) |
|
14.8 Synchronization in spread-spectrum systems |
|
|
745 | (12) |
|
14.8.1 The transmission system |
|
|
745 | (1) |
|
|
|
745 | (1) |
|
|
|
745 | (1) |
|
14.8.2 Timing estimators with feedback |
|
|
746 | (1) |
|
Non-data aided: non-coherent DLL |
|
|
747 | (1) |
|
Non-data aided modified code tracking loop |
|
|
747 | (1) |
|
Data and phase directed: coherent DLL |
|
|
747 | (10) |
|
14.9 Synchronization in OFDM |
|
|
751 | (1) |
|
14.9.1 Frame synchronization |
|
|
751 | (1) |
|
|
|
751 | (1) |
|
Schmidl and Cox algorithm |
|
|
752 | (2) |
|
14.9.2 Carrier frequency synchronization |
|
|
754 | (1) |
|
|
|
755 | (1) |
|
Other synchronization solutions |
|
|
755 | (1) |
|
14.10 Synchronization in SC-FDMA |
|
|
756 | (3) |
|
|
|
756 | (3) |
|
15 Self-training equalization |
|
|
759 | (25) |
|
15.1 Problem definition and fundamentals |
|
|
759 | (6) |
|
Minimization of a special function |
|
|
762 | (3) |
|
15.2 Three algorithms for PAM systems |
|
|
765 | (2) |
|
|
|
765 | (1) |
|
Benveniste-Goursat algorithm |
|
|
766 | (1) |
|
|
|
766 | (1) |
|
|
|
767 | (1) |
|
15.3 The contour algorithm for PAM systems |
|
|
767 | (3) |
|
Simplified realization of the contour algorithm |
|
|
769 | (1) |
|
15.4 Self-training equalization for partial response systems |
|
|
770 | (3) |
|
|
|
770 | (2) |
|
|
|
772 | (1) |
|
15.5 Self-training equalization for QAM systems |
|
|
773 | (6) |
|
|
|
773 | (2) |
|
15.5.1 Constant-modulus algorithm |
|
|
775 | (1) |
|
|
|
776 | (1) |
|
Joint contour algorithm and carrier phase tracking |
|
|
777 | (2) |
|
15.6 Examples of applications |
|
|
779 | (5) |
|
|
|
783 | (1) |
|
Appendix 15.A On the convergence of the contour algorithm |
|
|
784 | (47) |
|
16 Low-complexity demodulators |
|
|
787 | (44) |
|
|
|
787 | (6) |
|
|
|
787 | (2) |
|
Error probability of M-DPSK |
|
|
789 | (2) |
|
16.1.2 Differential encoding and coherent demodulation |
|
|
791 | (1) |
|
Differentially encoded BPSK |
|
|
791 | (1) |
|
|
|
791 | (2) |
|
16.2 (D)PSK non-coherent receivers |
|
|
793 | (5) |
|
16.2.1 Baseband differential detector |
|
|
793 | (1) |
|
16.2.2 IF-band (1 bit) differential detector |
|
|
794 | (2) |
|
Signal at detection point |
|
|
796 | (1) |
|
16.2.3 FM discriminator with integrate and dump filter |
|
|
797 | (1) |
|
16.3 Optimum receivers for signals with random phase |
|
|
798 | (9) |
|
|
|
799 | (1) |
|
Implementation of a non-coherent ML receiver |
|
|
800 | (4) |
|
Error probability for a non-coherent binary FSK system |
|
|
804 | (2) |
|
Performance comparison of binary systems |
|
|
806 | (1) |
|
16.4 Frequency-based modulations |
|
|
807 | (9) |
|
16.4.1 Frequency shift keying |
|
|
807 | (1) |
|
|
|
808 | (1) |
|
|
|
808 | (1) |
|
Limiter-discnnunator FM demodulator |
|
|
809 | (1) |
|
16.4.2 Minimum-shift keying |
|
|
810 | (2) |
|
Power spectral density of CPFSK |
|
|
812 | (2) |
|
|
|
814 | (1) |
|
MSK with differential precoding |
|
|
815 | (1) |
|
16.4.3 Remarks on spectral containment |
|
|
816 | (1) |
|
|
|
816 | (15) |
|
16.5.1 Implementation of a GMSK scheme |
|
|
819 | (2) |
|
|
|
821 | (1) |
|
|
|
821 | (1) |
|
|
|
822 | (2) |
|
16.5.2 Linear approximation of a GMSK signal |
|
|
824 | (1) |
|
|
|
824 | (5) |
|
Performance in the presence of multipath |
|
|
829 | (1) |
|
|
|
830 | (1) |
|
Appendix 16.A Continuous phase modulation |
|
|
831 | (59) |
|
Alternative definition of CPM |
|
|
831 | (1) |
|
|
|
832 | (1) |
|
17 Applications of interference cancellation |
|
|
833 | (24) |
|
17.1 Echo and near-end crosstalk cancellation for PAM systems |
|
|
834 | (8) |
|
Crosstalk cancellation and full-duplex transmission |
|
|
835 | (1) |
|
Polyphase structure of the canceller |
|
|
836 | (1) |
|
|
|
836 | (1) |
|
|
|
837 | (1) |
|
Canceller structure with distributed arithmetic |
|
|
838 | (4) |
|
17.2 Echo cancellation for QAM systems |
|
|
842 | (2) |
|
17.3 Echo cancellation for OFDM systems |
|
|
844 | (2) |
|
17.4 Multiuser detection for VDSL |
|
|
846 | (11) |
|
17.4.1 Upstream power back-off |
|
|
850 | (1) |
|
17.4.2 Comparison of PBO methods |
|
|
851 | (4) |
|
|
|
855 | (2) |
|
18 Examples of communication systems |
|
|
857 | (33) |
|
18.1 The 5G cellular system |
|
|
857 | (11) |
|
18.1.1 Cells in a wireless system |
|
|
857 | (1) |
|
18.1.2 The release 15 of the 3GPP standard |
|
|
858 | (1) |
|
18.1.3 Radio access network |
|
|
859 | (1) |
|
|
|
859 | (2) |
|
NR data transmission chain |
|
|
861 | (1) |
|
|
|
861 | (1) |
|
|
|
862 | (1) |
|
|
|
862 | (1) |
|
|
|
863 | (1) |
|
Initial access or beam sweeping |
|
|
864 | (1) |
|
|
|
865 | (1) |
|
Channel state information reporting |
|
|
865 | (1) |
|
|
|
865 | (1) |
|
Transform precoding numerology |
|
|
866 | (1) |
|
|
|
866 | (1) |
|
|
|
866 | (1) |
|
|
|
867 | (1) |
|
|
|
867 | (1) |
|
|
|
868 | (4) |
|
|
|
870 | (2) |
|
18.3 Wireless local area networks |
|
|
872 | (1) |
|
Medium access control protocols |
|
|
872 | (1) |
|
|
|
873 | (2) |
|
|
|
875 | (1) |
|
18.6 Transmission over unshielded twisted pairs |
|
|
875 | (6) |
|
18.6.1 Transmission over UTP in the customer service area |
|
|
876 | (4) |
|
18.6.2 High-speed transmission over UTP in local area networks |
|
|
880 | (1) |
|
18.7 Hybrid fibre/coaxial cable networks |
|
|
881 | (9) |
|
Ranging and power adjustment in OFDMA systems |
|
|
885 | (1) |
|
Ranging and power adjustment for uplink transmission |
|
|
886 | (3) |
|
|
|
889 | (1) |
|
|
|
890 | (1) |
|
|
|
890 | (1) |
|
Appendix 18.B Detenninistic access methods |
|
|
890 | (25) |
|
19 High-speed communications over twisted-pair cables |
|
|
893 | (22) |
|
19.1 Quaternary partial response class-IV system |
|
|
893 | (13) |
|
|
|
893 | (1) |
|
Received signal and adaptive gain control |
|
|
894 | (1) |
|
Near-end crosstalk cancellation |
|
|
895 | (1) |
|
|
|
895 | (1) |
|
|
|
895 | (1) |
|
Compensation of the timing phase drift |
|
|
896 | (1) |
|
Adaptive equalizer coefficient adaptation |
|
|
896 | (1) |
|
Convergence behaviour of the various algorithms |
|
|
897 | (1) |
|
19.1.1 VLSI implementation |
|
|
897 | (1) |
|
Adaptive digital NEXT canceller |
|
|
897 | (3) |
|
Adaptive digital equalizer |
|
|
900 | (4) |
|
|
|
904 | (2) |
|
|
|
906 | (1) |
|
|
|
906 | (9) |
|
|
|
906 | (2) |
|
|
|
908 | (1) |
|
|
|
909 | (3) |
|
19.2.1 Signal processing functions |
|
|
912 | (1) |
|
The 100BASE-T2 transmitter |
|
|
912 | (1) |
|
|
|
913 | (1) |
|
Computational complexity of digital receive filters |
|
|
914 | (1) |
|
|
|
915 | (1) |
|
Appendix 19.A Interference suppression |
|
|
915 | (2) |
| Index |
|
917 | |
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