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Radio Access Network Slicing and Virtualization for 5G Vertical Industries


Radio Access Network Slicing and Virtualization for 5G Vertical Industries


IEEE Press 1. Aufl.

von: Lei Zhang, Arman Farhang, Gang Feng, Oluwakayode Onireti

113,99 €

Verlag: Wiley
Format: EPUB
Veröffentl.: 01.12.2020
ISBN/EAN: 9781119652472
Sprache: englisch
Anzahl Seiten: 320

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Beschreibungen

<p><b>Learn </b><b>how radio access network (RAN) slicing allows 5G networks to adapt to a wide range of environments in this masterful resource</b></p> <p><i>Radio Access Network Slicing and Virtualization for 5G Vertical Industries</i>provides readers with a comprehensive and authoritative examination of crucial topics in the field of radio access network (RAN) slicing. Learn from renowned experts as they detail how this technology supports and applies to various industrial sectors, including manufacturing, entertainment, public safety, public transport, healthcare, financial services, automotive, and energy utilities.</p> <p><i>Radio Access Network Slicing and Virtualization for 5G Vertical Industries </i>explains how future wireless communication systems must be built to handle high degrees of heterogeneity, including different types of applications, device classes, physical environments, mobility levels, and carrier frequencies. The authors describe how RAN slicing can be utilized to adapt 5G technologies to such wide-ranging circumstances.</p> <p>The book covers a wide range of topics necessary to understand RAN slicing, including:</p> <ul> <li>Physical waveforms design</li> <li>Multiple service signals coexistence</li> <li>RAN slicing and virtualization</li> <li>Applications to 5G vertical industries in a variety of environments</li> </ul> <p>This book is perfect for telecom engineers and industry actors who wish to identify realistic and cost-effective concepts to support specific 5G verticals. It also belongs on the bookshelves of researchers, professors, doctoral, and postgraduate students who want to identify open issues and conduct further research.</p>
<p>About the Editors xiii</p> <p>Preface xvii</p> <p>List of Contributors xxiii</p> <p>List of Abbreviations xxvii</p> <p><b>Part I Waveforms and Mixed-Numerology </b><b>1</b></p> <p><b>1 ICI Cancellation Techniques Based on Data Repetition for OFDM Systems </b><b>3<br /></b><i>Miaowen Wen, Jun Li, Xilin Cheng and Xiang Cheng</i></p> <p>1.1 OFDM History 3</p> <p>1.2 OFDM Principle 4</p> <p>1.2.1 Subcarrier Orthogonality 4</p> <p>1.2.2 Discrete Implementation 5</p> <p>1.2.3 OFDM in Multipath Channel 6</p> <p>1.3 Carrier Frequency Offset Effect 8</p> <p>1.3.1 Properties of ICI Coefficients 9</p> <p>1.3.2 Carrier-to-Interference Power Ratio 9</p> <p>1.4 ICI Cancellation Techniques 11</p> <p>1.4.1 One-Path Cancellation with Mirror Mapping 11</p> <p>1.4.1.1 MSR Scheme 12</p> <p>1.4.1.2 MCSR Scheme 13</p> <p>1.4.2 Two-Path Cancellation with Mirror Mapping 14</p> <p>1.4.2.1 MCVT Scheme 15</p> <p>1.4.2.2 MCJT Scheme 15</p> <p>1.4.3 CIR Comparison 16</p> <p>1.5 Experiment on Sea 17</p> <p>1.5.1 Experiment Settings 18</p> <p>1.5.2 Experiment Results 21</p> <p>1.6 Summary 22</p> <p>References 23</p> <p><b>2 Filtered OFDM: An Insight into Intrinsic In-Band Interference </b><b>25<br /></b><i>Juquan Mao, Lei Zhang and Pei Xiao</i></p> <p>2.1 Introduction 25</p> <p>2.1.1 Notations 26</p> <p>2.2 System Model for f-OFDM SISO System 26</p> <p>2.3 In-Band Interference Analysis and Discussion 30</p> <p>2.3.1 Channel Diagonalization and In-Band Interference-Free Systems 30</p> <p>2.3.2 In-Band Interference Power 31</p> <p>2.3.3 In-Band Interference Mitigation: A Practical Approach for Choosing CR Length 32</p> <p>2.3.4 An Alternative for In-Band Interference Mitigation: Frequency Domain Equalization (FDE) 33</p> <p>2.3.4.1 Linear Equalizers 33</p> <p>2.3.4.2 Nonlinear Equalizers 34</p> <p>2.4 Numerical Results 34</p> <p>2.4.1 Numerical Results for In-Band Interference 35</p> <p>2.5 Conclusion 38</p> <p>1.2 Appendix 38</p> <p>1.2.1 Derivation of z<i><sub>k</sub> </i>38</p> <p>2.3 Appendix 39</p> <p>2.3.1 Proof of 𝚯<sub>pre</sub>Being a Strict Upper Triangle 39</p> <p>3.4 Appendix 39</p> <p>3.4.1 Proof of Property 2.A.2 39</p> <p>References 40</p> <p><b>3 Windowed OFDM for Mixed-Numerology 5G and Beyond Systems </b><b>43<br /></b><i>Bowen Yang, Xiaoying Zhang, Lei Zhang, Arman Farhang, Pei Xiao and Muhammad Ali Imran</i></p> <p>3.1 Introduction 43</p> <p>3.2 W-OFDM System Model 45</p> <p>3.2.1 Single Numerology System Model 46</p> <p>3.2.2 System Model for Mixed Numerologies 48</p> <p>3.3 Inter-numerology Interference Analysis 50</p> <p>3.3.1 Inter-numerology Interference Analysis for Numerology 1 50</p> <p>3.3.2 Inter-numerology Interference Analysis for Numerology 2 52</p> <p>3.4 Numerical Results and Discussion 54</p> <p>3.5 Conclusions 57</p> <p>3.6 Derivation of (3.9) 57</p> <p>3.7 Derivations of (3.28) 58</p> <p>3.8 Derivations of (3.30) 59</p> <p>References 59</p> <p><b>4 Generalized Frequency Division Multiplexing: Unified Multicarrier Framework </b><b>63<br /></b><i>Ahmad Nimr, Zhongju Li, Marwa Chafii and Gerhard Fettweis</i></p> <p>4.1 Overview of MulticarrierWaveforms 63</p> <p>4.1.1 Time–Frequency Representation 64</p> <p>4.1.1.1 Discrete-Time Representation 65</p> <p>4.1.1.2 Relation to Gabor Theory 66</p> <p>4.1.2 GFDM As a FlexibleWaveform 66</p> <p>4.1.2.1 GFDM with Multiple Prototype Pulses 67</p> <p>4.1.3 Generalized Block-Based Multicarrier 68</p> <p>4.1.3.1 Transmitter 69</p> <p>4.1.3.2 Receiver 69</p> <p>4.2 GFDM As a Flexible Framework 70</p> <p>4.2.1 GFDM Representations 71</p> <p>4.2.1.1 Filter Bank Representation 71</p> <p>4.2.1.2 Vector Representation 71</p> <p>4.2.1.3 2D-Block Representation 72</p> <p>4.2.1.4 GFDM Matrix Structure 73</p> <p>4.2.2 Architecture and Extended Flexibility 74</p> <p>4.2.2.1 Alternative Interpretation of GFDM 75</p> <p>4.2.2.2 Extended Flexibility 76</p> <p>4.2.2.3 Flexible Hardware Architecture 76</p> <p>4.3 GFDM for OFDM Enhancement 78</p> <p>4.3.1 Transmitter 78</p> <p>4.3.2 Receiver 79</p> <p>4.3.2.1 LMMSE GFDM-Based Receiver 79</p> <p>4.4 Conclusions 80</p> <p>References 80</p> <p><b>5 Filter Bank Multicarrier Modulation </b><b>83<br /></b><i>Behrouz Farhang-Boroujeny</i></p> <p>5.1 Introduction 83</p> <p>5.1.1 Notations: 83</p> <p>5.2 FBMC Methods 84</p> <p>5.3 Theory 84</p> <p>5.3.1 CMT 85</p> <p>5.3.2 SMT 88</p> <p>5.4 Prototype Filter Design 92</p> <p>5.4.1 Prototype Filters for Time-Invariant Channels 92</p> <p>5.4.2 Prototype Filters for Time-Varying Channels 93</p> <p>5.5 Synchronization and Tracking Methods 94</p> <p>5.5.1 Preamble Design 95</p> <p>5.5.2 Channel Tracking 96</p> <p>5.5.3 Timing Tracking 97</p> <p>5.6 Equalization 97</p> <p>5.7 Computational Complexity 98</p> <p>5.8 Applications 98</p> <p>References 99</p> <p><b>6 Orthogonal Time–Frequency Space Modulation: Principles and Implementation </b><b>103<br /></b><i>Arman Farhang and Behrouz Farhang-Boroujeny</i></p> <p>6.1 Introduction 103</p> <p>6.2 OTFS Principles 105</p> <p>6.3 OFDM-Based OTFS 107</p> <p>6.4 Channel Impact 108</p> <p>6.5 Simplified Modem Structure 110</p> <p>6.6 Complexity Analysis 113</p> <p>6.7 Recent Results and Potential Research Directions 114</p> <p>References 117</p> <p><b>Part II RAN Slicing and 5G Vertical Industries </b><b>121</b></p> <p><b>7 Multi-Numerology Waveform Parameter Assignment in 5G </b><b>123<br /></b><i>Ahmet Yazar and Hüseyin Arslan</i></p> <p>7.1 Introduction 123</p> <p>7.1.1 Problem Definitions 125</p> <p>7.1.2 Literature Review 126</p> <p>7.2 Waveform Parameter Options 128</p> <p>7.3 Waveform Parameter Assignment 130</p> <p>7.4 Conclusion 132</p> <p>References 132</p> <p><b>8 Network Slicing with Spectrum Sharing </b><b>137<br /></b><i>Yue Liu, Xu Yang and Laurie Cuthbert</i></p> <p>8.1 The Need for Spectrum Sharing 137</p> <p>8.2 Historical Approaches to Spectrum Sharing 139</p> <p>8.2.1 Classifications of Spectrum Sharing 140</p> <p>8.2.1.1 Orthogonality 140</p> <p>8.2.1.2 Sharing Rights 141</p> <p>8.2.1.3 Allocation of Resources 142</p> <p>8.3 Network Slicing in the RAN 144</p> <p>8.4 Radio Resource Allocation that Considers Spectrum Sharing 146</p> <p>8.4.1 Example Radio Resource Allocation for Sharing Through Network Slicing 147</p> <p>8.4.2 Other Considerations 153</p> <p>8.5 Isolation 156</p> <p>8.5.1 Example Isolation Results Using CAC 157</p> <p>8.5.1.1 Type A: Baseline – CACWithout Network Isolation and Without Protection for Existing Users 158</p> <p>8.5.1.2 Type B: Optimum Types – B1 and B2 158</p> <p>8.5.1.3 Type C: Without Compensation – C1 and C2 159</p> <p>8.6 Conclusions 162</p> <p>Acknowledgments 163</p> <p>References 163</p> <p><b>9 Access Control and Handoff Policy Design for RAN Slicing </b><b>167<br /></b><i>Yao Sun, Lei Zhang, Gang Feng and Muhammad Ali Imran</i></p> <p>9.1 A Framework of User Access Control for RAN Slicing 167</p> <p>9.1.1 System Model for RAN Slicing 168</p> <p>9.1.2 UE Association Problem Description 170</p> <p>9.1.3 Admission Control Mechanisms Design for RAN Slicing 170</p> <p>9.1.3.1 Optimal QoS AC Mechanism 171</p> <p>9.1.3.2 Num-AC Mechanism 176</p> <p>9.1.4 Experiments, Results, and Discussions 177</p> <p>9.2 Smart Handoff Policy Design for RAN Slicing 179</p> <p>9.2.1 RAN Slice Based Mobile Network Model 179</p> <p>9.2.2 Multi-Agent Reinforcement Learning Based Handoff Framework 181</p> <p>9.2.3 LESS Algorithm for Target BS and NS Selection 181</p> <p>9.2.3.1 <i>q</i>-Value Update Policy 182</p> <p>9.2.3.2 Optimal Action Policy 183</p> <p>9.2.4 Experiment, Results, and Discussions 184</p> <p>9.3 Summary 186</p> <p>References 186</p> <p><b>10 Robust RAN Slicing </b><b>189<br /></b><i>Ruihan Wen and Gang Feng</i></p> <p>10.1 Introduction 189</p> <p>10.2 Network Model 190</p> <p>10.2.1 Slice Failure Detection Process 190</p> <p>10.2.2 System Model 191</p> <p>10.3 Robust RAN Slicing 193</p> <p>10.3.1 Failure Recovery Problem Formulation 193</p> <p>10.3.2 Robust RAN Slicing Problem Formulation 195</p> <p>10.3.3 Variable Neighborhood Search Based Heuristic for Robust RAN Slicing 196</p> <p>10.4 Numerical Results 199</p> <p>10.4.1 Performance Metrics 199</p> <p>10.4.2 Simulation Scenarios and Settings 200</p> <p>10.4.3 Results 201</p> <p>10.5 Conclusions and Future Work 206</p> <p>References 206</p> <p><b>11 Flexible Function Split Over Ethernet Enabling RAN Slicing </b><b>209<br /></b><i>Ghizlane Mountaser and Toktam Mahmoodi</i></p> <p>11.1 Flexible Functional Split Toward RAN Slicing 209</p> <p>11.1.1 Full Centralization and CPRI 209</p> <p>11.1.2 RAN Functional Split 210</p> <p>11.1.3 Flexible Functional Split as RAN Slicing Enabler 213</p> <p>11.2 Fronthaul Reliability and Slicing by Deploying Multipath at the Fronthaul 213</p> <p>11.2.1 Packet-Based Fronthaul 213</p> <p>11.2.2 Multipath Packet-Based Fronthaul for Enhancing Reliability 213</p> <p>11.2.3 Slicing Within Multipath Fronthaul 214</p> <p>11.3 Experimentation Results Evaluation of Flexible Functional Split for RAN Slicing 214</p> <p>11.3.1 Experimental Setup 214</p> <p>11.3.2 Evaluation and Discussion of the Results 215</p> <p>11.4 Simulation Results Analysis of Multipath Packet-Based Fronthaul for RAN Slicing 217</p> <p>11.4.1 Simulation System Model 217</p> <p>References 219</p> <p><b>12 Service-Oriented RAN Support of Network Slicing </b><b>221<br /></b><i>Wei Tan, Feng Han, Yinghao Jin and Chenchen Yang</i></p> <p>12.1 Introduction 221</p> <p>12.2 General Concept and Principles 222</p> <p>12.2.1 Network Slicing Concepts 223</p> <p>12.2.2 Overall RAN Subsystem 224</p> <p>12.2.3 Key Principles of Network Slicing in RAN 225</p> <p>12.3 RAN Subsystem Deployment Scenarios 227</p> <p>12.4 Key Technologies to Enable Service-Oriented RAN Slicing 229</p> <p>12.4.1 Device Awareness of RAN Part of Network Slice 230</p> <p>12.4.2 Slice-Specific RAN Part of Network Slice 232</p> <p>12.4.3 Mission-Driven Resource Utilization, Sharing, and Aggregation 234</p> <p>12.4.4 Slice-Aware Connected UE Mobility 235</p> <p>12.4.5 Slice-Level Handlings for Idle/Inactive UEs 237</p> <p>12.5 Summary 237</p> <p>References 238</p> <p><b>13 5G Network Slicing for V2X Communications: Technologies and Enablers </b><b>239<br /></b><i>Claudia Campolo, Antonella Molinaro and Vincenzo Sciancalepore</i></p> <p>13.1 Introduction 239</p> <p>13.2 Vehicular Applications 240</p> <p>13.3 V2X Communication Technologies 241</p> <p>13.3.1 The C-V2X Technology 242</p> <p>13.3.1.1 The PC5 Radio Interface 242</p> <p>13.3.1.2 The LTE-Uu Interface 242</p> <p>13.3.1.3 Core Network 243</p> <p>13.3.2 C-V2X Toward 5G 243</p> <p>13.3.2.1 Radio Interface 243</p> <p>13.3.2.2 Core Network 244</p> <p>13.4 Cloudification in V2X Environments 245</p> <p>13.4.1 The Role of MEC 245</p> <p>13.4.2 ETSI MEC-Based Programmable Interfaces 246</p> <p>13.4.3 MEC-Based Support for V2X Applications 247</p> <p>13.5 Transport and Tunneling Protocol for V2X 248</p> <p>13.5.1 GTP-U Encapsulation 248</p> <p>13.5.2 Segment Routing v6 248</p> <p>13.5.3 Scalability and Flexibility in SRv6 250</p> <p>13.6 Network Slicing for V2X 251</p> <p>13.6.1 3GPP Specifications 251</p> <p>13.6.2 Literature Overview 252</p> <p>13.7 Lessons Learnt and Guidelines 255</p> <p>13.7.1 Slice Mapping and Identification 255</p> <p>13.7.2 Multi-tenancy Management 255</p> <p>13.7.3 Massive Communications 255</p> <p>13.7.4 Transparent Mobility 256</p> <p>13.7.5 Isolation 256</p> <p>13.8 Conclusions 256</p> <p>References 256</p> <p><b>14 Optimizing Resource Allocation in URLLC for Real-Time Wireless Control Systems </b><b>259<br /></b><i>Bo Chang, Liying Li and Guodong Zhao</i></p> <p>14.1 Introduction 259</p> <p>14.2 System Model with Latency and Reliability Constraints 261</p> <p>14.2.1 Wireless Control Model 262</p> <p>14.2.2 Wireless Communication Model 266</p> <p>14.3 Communication-Control Co-Design 267</p> <p>14.3.1 Communication Constraint 267</p> <p>14.3.2 Control Constraint 268</p> <p>14.3.3 Problem Formulation 269</p> <p>14.4 Optimal Resource Allocation for The Proposed Co-Design 270</p> <p>14.4.1 Relationship Between Control and Communication 270</p> <p>14.4.2 Optimal Resource Allocation 271</p> <p>14.4.2.1 Problem Conversion 271</p> <p>14.4.2.2 Problem Solution 272</p> <p>14.4.3 Optimal Control Convergence Rate 273</p> <p>14.5 Simulations Results 273</p> <p>14.5.1 Control Performance 274</p> <p>14.5.2 Communication Performance 276</p> <p>14.6 Conclusions 279</p> <p>References 279</p> <p>Index 283 </p>
<p><b>LEI ZHANG,</b> PhD, is Senior Lecturer at the University of Glasgow, UK. He received his PhD degree from the University of Sheffield, UK. He was a research fellow in the 5G Innovation Centre (5GIC) at the Institute of Communications (ICS), University of Surrey, UK. His research interests include wireless communication systems and networks, blockchain technology, radio access network slicing (RAN slicing), Internet of Things (IoT), multi-antenna signal processing, MIMO systems, and many more. <p><b>ARMAN FARHANG,</b> PhD, received his PhD from the Trinity College in Dublin, Ireland. He is currently an Assistant Professor in the Department of Electronic Engineering at Maynooth University, Ireland. His research interests and activities are in the broad area of signal processing for communications, waveform design, signal processing for multiuser and multiple antenna systems. <p><b>GANG FENG,</b> PhD, is a Professor at the University of Electronic Science and Technology of China (UESTC), China. He received his MEng degree in Electronic Engineering from UESTC and his PhD in information engineering from the Chinese University of Hong Kong. <p><b>OLUWAKAYODE ONIRETI,</b> PhD, is a Lecturer at the University of Glasgow, UK. He received an MSc degree in mobile and satellite communication and a PhD in Electronics Engineering from the University of Surrey, Guildford, UK.
<p><b>Learn how radio access network (RAN) slicing allows 5G networks to adapt to a wide range of environments in this masterful resource</b> <p><i>Radio Access Network Slicing and Virtualization for 5G Vertical Industries</i> provides readers with a comprehensive and authoritative examination of crucial topics in the field of radio access network (RAN) slicing. Learn from renowned experts as they detail how this technology supports and applies to various industrial sectors, including manufacturing, entertainment, public safety, public transport, healthcare, financial services, automotive, and energy utilities. <p><i>Radio Access Network Slicing and Virtualization for 5G Vertical Industries</i> explains how future wireless communication systems must be built to handle high degrees of heterogeneity, including different types of applications, device classes, physical environments, mobility levels, and carrier frequencies. The authors describe how RAN slicing can be utilized to adapt 5G technologies to such wide-ranging circumstances. <p>The book covers a wide range of topics necessary to understand RAN slicing, including: <ul> <li>Physical waveforms design</li> <li>Multiple service signals coexistence</li> <li>RAN slicing and virtualization</li> <li>Applications to 5G vertical industries in a variety of environments</li> </ul> <p>This book is perfect for telecom engineers and industry actors who wish to identify realistic and cost-effective concepts to support specific 5G verticals. It also belongs on the bookshelves of researchers, professors, doctoral, and postgraduate students who want to identify open issues and conduct further research.

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