About the editors |
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xiii | |
Preface |
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xv | |
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Part I EMF evaluation and characterisation |
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1 | (140) |
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1 EMF exposure definition, metrics, effects and regulations |
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3 | (20) |
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3 | (1) |
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1.2 Factors contributing to EM exposure in mobile communications |
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4 | (3) |
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1.2.1 Communication network topology |
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4 | (2) |
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1.2.2 Location of the user relative to the BS |
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6 | |
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1.2.3 Duration of exposure |
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5 | (2) |
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1.3 EM radiation and RF communication spectrum range |
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7 | |
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3 | (7) |
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8 | (2) |
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1.4.2 Far field and power density |
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10 | (1) |
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10 | (1) |
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1.6 Perception and physiological impact of EMF exposure in mobile communication |
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11 | (2) |
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1.6.1 Risk assessment and public perception of exposure |
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11 | (1) |
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1.6.2 Physiological impact |
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12 | (1) |
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1.7 EM exposure guidelines and limits |
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13 | (4) |
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14 | (2) |
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1.7.2 Precautionary principle |
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16 | |
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1.7.3 EM radiation exclusion zones |
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15 | (2) |
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17 | (6) |
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17 | (6) |
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2 Electromagnetic field (EMF) monitoring tools |
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23 | (30) |
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24 | (4) |
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2.1.1 EMF exposure metrics |
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25 | (1) |
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2.1.2 Typical EMF measurement sensor |
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26 | (2) |
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2.2 State of the art for EMF monitoring tools |
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28 | (18) |
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2.2.1 SAR measurement systems |
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28 | (2) |
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2.2.2 Power density/E-field measurement systems |
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30 | (11) |
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2.2.3 Simulation tools for EMF monitoring |
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41 | (2) |
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2.2.4 Other measurement tools |
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43 | (3) |
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2.3 EMF monitoring of a smart city |
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46 | (3) |
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2.4 Conclusions and perspectives |
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49 | (4) |
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50 | (3) |
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3 Large-scale EMF characterization considering real network deployments |
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53 | (3) |
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56 | (1) |
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3.1.1 Low-complexity dosimeter |
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56 | (1) |
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57 | (2) |
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3.1.3 Dosimeter integration |
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59 | (4) |
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3.2 Scenario characterization |
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63 | (1) |
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3.2.1 Deployment dimensioning |
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63 | (1) |
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64 | (3) |
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3.2.3 Uplink--downlink correlation |
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65 | (2) |
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3.3 Calibration of the measurements |
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67 | (4) |
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3.3.1 Monaxial to isotropic |
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68 | (1) |
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3.3.2 Location extrapolation factor |
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69 | (1) |
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3.3.3 Indoor-outdoor extrapolation factor |
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70 | (1) |
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3.4 Exposure calculation methodology |
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71 | (5) |
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76 | (5) |
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3.5.1 Frequency selectivity |
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76 | (2) |
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3.5.2 Geographical and temporal variation |
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78 | (1) |
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79 | (2) |
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81 | (4) |
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82 | (3) |
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4 EMF exposure in heterogeneous networks environments |
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85 | (30) |
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85 | (1) |
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4.2 EMF exposure evaluation and assessment |
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86 | (6) |
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4.2.1 Dosimetric/epidemiologic use of metrics |
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86 | (2) |
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4.2.2 Methods for EMF exposure assessment |
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88 | (4) |
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92 | (8) |
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4.3.1 Estimation of EMF from personal and fixed-point exposimeters |
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92 | (3) |
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95 | (4) |
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4.3.3 EMF exposure in BANs |
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99 | (1) |
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4.4 EMF exposure in heterogeneous networks |
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100 | (8) |
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4.4.1 Exposure assessment in heterogeneous networks accounting for UL and DL |
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100 | (1) |
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100 | (2) |
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4.4.3 Simulation scenario |
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102 | (1) |
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102 | (6) |
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108 | (7) |
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109 | (6) |
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5 Architecture of public mobile networks and its impact on EMF exposure |
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115 | (26) |
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115 | (1) |
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5.2 Network architecture layers: macro, micro, pico, femto |
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116 | (4) |
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118 | (1) |
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119 | (1) |
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5.3 Measurements of incident EMF in DL |
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120 | (2) |
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5.4 Measurements of Tx power in UL |
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122 | (5) |
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5.5 Case studies: macro/micro, macro/femto |
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127 | (6) |
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5.5.1 The addition of the microcell and indoor DAS system |
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128 | (4) |
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5.5.2 Femtocell vs. macrocell |
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132 | (1) |
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5.6 Impact of specific user services to EMF exposure |
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133 | (4) |
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137 | (4) |
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137 | (4) |
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Part II EMF reduction techniques |
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141 | (136) |
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6 EMF emission-aware resource allocation for uplink OFDM systems |
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143 | (24) |
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143 | (1) |
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144 | (2) |
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6.3 EMF emission reduction schemes |
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146 | (8) |
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6.3.1 Offline EMF emission reduction scheme |
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147 | (4) |
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6.3.2 Online EMF emission reduction scheme |
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151 | (2) |
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6.3.3 Complexity analysis |
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153 | (1) |
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154 | (8) |
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162 | (5) |
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163 | (4) |
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7 Multicell uplink scheduling for EMF emission minimization in OFDMA systems |
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167 | (18) |
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167 | (1) |
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168 | (2) |
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7.3 MC EMF emission-aware scheduling scheme |
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170 | (7) |
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7.3.1 Subcarrier allocation |
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171 | (1) |
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172 | (3) |
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7.3.3 Scheduler algorithm |
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175 | (2) |
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177 | (1) |
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7.5 Numerical results and discussions |
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178 | (5) |
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183 | (2) |
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184 | (1) |
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8 EMF: RF device end of things -- low-exposure user terminal radio design concepts |
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185 | (22) |
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8.1 Historical context: design of low SAR antennas for voice mobile |
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186 | (4) |
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8.2 Emergence of ubiquitous computing and the changed shape of wireless device usage |
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190 | (2) |
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8.3 Low-exposure antenna technologies in advanced mobile terminals |
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192 | (7) |
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8.3.1 Context-aware multiple antennas |
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194 | (3) |
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8.3.2 Proximity slave device for mobile terminals |
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197 | (2) |
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8.4 Societal changes in mobile terminal usage |
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199 | (1) |
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8.5 Low-exposure transmission techniques for advanced mobile terminals |
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200 | (1) |
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8.6 Conclusions and evaluation of candidate low-exposure technologies for the mobile terminal |
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201 | (6) |
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202 | (5) |
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9 Millimetre-wave flexible wearable antenna design and challenges for 5G and beyond |
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207 | (24) |
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9.1 Millimetre-wave spectrum for 5G networks |
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208 | (1) |
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9.2 High-frequency spectrum challenges for 5G |
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209 | (2) |
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9.3 Antennas for 5G cellular networks |
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211 | (1) |
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9.4 5G antennas interaction with human body |
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211 | (2) |
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9.5 Flexible antennas for 5G wearable applications |
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213 | (1) |
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9.6 Fabrication processes for flexible antennas |
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214 | (4) |
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9.6.1 Laser milling and PCB prototyping |
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214 | (1) |
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215 | (1) |
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216 | (1) |
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217 | (1) |
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9.7 Design and implementation of flexible 5G antenna |
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218 | (8) |
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9.7.1 Antenna design and fabrication |
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218 | (4) |
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9.7.2 Numerical and experimental analysis |
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222 | (4) |
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226 | (5) |
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226 | (5) |
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10 Reducing EMF emissions in ultra-reliable low-latency communications with HARQ |
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231 | (20) |
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Joao Pedro Battistella Nadas |
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10.1 Hybrid automatic repeat request |
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232 | (5) |
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10.2 Reducing EMF emission |
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237 | (11) |
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10.2.1 Health concerns from EMF exposure |
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237 | (1) |
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10.2.2 Reducing EMF radiation in URLLC applications |
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238 | (10) |
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248 | (3) |
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248 | (3) |
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11 Reducing EMF via energy-efficient inter-frequency small cell discovery |
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251 | (24) |
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251 | (1) |
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11.2 Energy-efficient ISCD mechanisms |
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252 | (4) |
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11.2.1 Relaxed inter-frequency measurement gap |
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253 | (1) |
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11.2.2 UE speed-based inter-frequency measurement gap triggering |
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253 | (2) |
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11.2.3 Use of RSS or RSRP radio fingerprint for ISCD |
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255 | (1) |
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11.3 Inter-frequency small cell discovery |
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256 | (4) |
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11.3.1 ISCD periodicity and small cell offloading opportunity |
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257 | (2) |
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11.3.2 Approximation of the percentage of time a typical UE missed small cell offloading opportunity |
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259 | (1) |
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11.4 Energy efficiency evaluation |
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260 | (8) |
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11.4.1 Probability of UE association to a tier |
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261 | (3) |
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11.4.2 Ideal average energy efficiency |
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264 | (1) |
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11.4.3 Realistic average energy efficiency |
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264 | (4) |
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11.5 Optimal ISCD periodicity |
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268 | (5) |
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11.5.1 Optimal ISCD based on average energy consumption |
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268 | (1) |
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11.5.2 Optimal ISCD based on UE's average energy efficiency |
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269 | (4) |
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273 | (2) |
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273 | (2) |
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12 Conclusion and future perspectives |
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275 | (2) |
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Index |
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277 | |