UAV communications for 5G and beyond:
Gespeichert in:
| Weitere Verfasser: | , , , , |
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| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Hoboken, NJ
Wiley
2021
[Piscataway Township, New Jersey, USA] IEEE Press |
| Online-Zugang: | FHI01 TUM01 |
| Beschreibung: | Description based on publisher supplied metadata and other sources |
| Beschreibung: | 1 Online-Ressource (xxiv, 440 Seiten) Illustrationen, Diagramme |
| ISBN: | 9781119575672 9781119575726 9781119575795 |
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| 245 | 1 | 0 | |a UAV communications for 5G and beyond |c edited by Yong Zeng, Ismail Guvenc, Rui Zhang, Giovanni Geraci, David W. Matolak |
| 264 | 1 | |a Hoboken, NJ |b Wiley |c 2021 | |
| 264 | 1 | |a [Piscataway Township, New Jersey, USA] |b IEEE Press | |
| 264 | 4 | |c © 2021 | |
| 300 | |a 1 Online-Ressource (xxiv, 440 Seiten) |b Illustrationen, Diagramme | ||
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| 500 | |a Description based on publisher supplied metadata and other sources | ||
| 505 | 8 | |a Cover -- Title Page -- Copyright -- Contents -- List of Contributors -- Acronyms -- Part I Fundamentals of UAV Communications -- Chapter 1 Overview -- 1.1 UAV Definitions, Classes, and Global Trend -- 1.2 UAV Communication and Spectrum Requirement -- 1.3 Potential Existing Technologies for UAV Communications -- 1.3.1 Direct Link -- 1.3.2 Satellite -- 1.3.3 Ad‐Hoc Network -- 1.3.4 Cellular Network -- 1.4 Two Paradigms in Cellular UAV Communications -- 1.4.1 Cellular‐Connected UAVs -- 1.4.2 UAV‐Assisted Wireless Communications -- 1.5 New Opportunities and Challenges -- 1.5.1 High Altitude -- 1.5.2 High LoS Probability -- 1.5.3 High 3D Mobility -- 1.5.4 SWAP Constraints -- 1.6 Chapter Summary and Main Organization of the Book -- References -- Chapter 2 A Survey of Air‐to‐Ground Propagation Channel Modeling for Unmanned Aerial Vehicles -- 2.1 Introduction -- 2.2 Literature Review -- 2.2.1 Literature Review on Aerial Propagation -- 2.2.2 Existing Surveys on UAV AG Propagation -- 2.3 UAV AG Propagation Characteristics -- 2.3.1 Comparison of UAV AG and Terrestrial Propagation -- 2.3.2 Frequency Bands for UAV AG Propagation -- 2.3.3 Scattering Characteristics for AG Propagation -- 2.3.4 Antenna Configurations for AG Propagation -- 2.3.5 Doppler Effects -- 2.4 AG Channel Measurements: Configurations, Challenges, Scenarios, and Waveforms -- 2.4.1 Channel Measurement Configurations -- 2.4.2 Challenges in AG Channel Measurements -- 2.4.3 AG Propagation Scenarios -- 2.4.3.1 Open Space -- 2.4.3.2 Hilly/Mountainous -- 2.4.3.3 Forest -- 2.4.3.4 Water/Sea -- 2.4.4 Elevation Angle Effects -- 2.5 UAV AG Propagation Measurement and Simulation Results in the Literature -- 2.5.1 Path Loss/Shadowing -- 2.5.2 Delay Dispersion -- 2.5.3 Narrowband Fading and Ricean K‐factor -- 2.5.4 Doppler Spread -- 2.5.5 Effects of UAV AG Measurement Environment | |
| 505 | 8 | |a 2.5.5.1 Urban/Suburban -- 2.5.5.2 Rural/Open Field -- 2.5.5.3 Mountains/Hilly, Over Sea, Forest -- 2.5.6 Simulations for Channel Characterization -- 2.6 UAV AG Propagation Models -- 2.6.1 AG Propagation Channel Model Types -- 2.6.2 Path‐Loss and Large‐Scale Fading Models -- 2.6.2.1 Free‐Space Path‐Loss Model -- 2.6.2.2 Floating‐Intercept Path‐Loss Model -- 2.6.2.3 Dual‐Slope Path‐Loss Model -- 2.6.2.4 Log‐Distance Path‐Loss Model -- 2.6.2.5 Modified FSPL Model -- 2.6.2.6 Two‐Ray PL Model -- 2.6.2.7 Log‐Distance FI Model -- 2.6.2.8 LOS/NLOS Mixture Path‐Loss Model -- 2.6.3 Airframe Shadowing -- 2.6.4 Small‐Scale Fading Models -- 2.6.5 Intermittent MPCs -- 2.6.6 Effect of Frequency Bands on Channel Models -- 2.6.7 MIMO AG Propagation Channel Models -- 2.6.8 Comparison of Different AG Channel Models -- 2.6.8.1 Large‐Scale Fading Models -- 2.6.8.2 Small‐Scale Fading Models -- 2.6.9 Comparison of Traditional Channel Models with UAV AG Propagation Channel Models -- 2.6.10 Ray Tracing Simulations -- 2.6.11 3GPP Channel Models for UAVs -- 2.7 Conclusions -- References -- Chapter 3 UAV Detection and Identification -- 3.1 Introduction -- 3.2 RF‐Based UAV Detection Techniques -- 3.2.1 RF Fingerprinting Technique -- 3.2.2 WiFi Fingerprinting Technique -- 3.3 Multistage UAV RF Signal Detection -- 3.3.1 Preprocessing Step: Multiresolution Analysis -- 3.3.2 The Naive Bayesian Decision Mechanism for RF Signal Detection -- 3.3.3 Detection of WiFi and Bluetooth Interference -- 3.4 UAV Classification Using RF Fingerprints -- 3.4.1 Feature Selection Using Neighborhood Components Analysis (NCA) -- 3.5 Experimental Results -- 3.5.1 Experimental Setup -- 3.5.2 Detection Results -- 3.5.3 UAV Classification Results -- 3.6 Conclusion -- Acknowledgments -- References -- Part II Cellular‐Connected UAV Communications -- Chapter 4 Performance Analysis for Cellular‐Connected UAVs | |
| 505 | 8 | |a 4.1 Introduction -- 4.1.1 Motivation -- 4.1.2 Related Works -- 4.1.3 Contributions and Chapter Structure -- 4.2 Modelling Preliminaries -- 4.2.1 Stochastic Geometry -- 4.2.2 Network Architecture -- 4.2.3 Channel Model -- 4.2.4 Blockage Modeling and LoS Probability -- 4.2.5 User Association Strategy and Link SINR -- 4.3 Performance Analysis -- 4.3.1 Exact Coverage Probability -- 4.3.2 Approximations for UAV Coverage Probability -- 4.3.2.1 Discarding NLoS and Noise Effects -- 4.3.2.2 Moment Matching -- 4.3.3 Achievable Throughput and Area Spectral Efficiency Analysis -- 4.4 System Design: Study Cases and Discussion -- 4.4.1 Analysis of Accuracy -- 4.4.2 Design Parameters -- 4.4.2.1 Impact of UAV Altitude -- 4.4.2.2 Impact of UAV Antenna Beamwidth -- 4.4.2.3 Impact of UAV Antenna Tilt -- 4.4.2.4 Impact of Different Types of Environment -- 4.4.3 Heterogeneous Networks - Tier Selection -- 4.4.4 Network Densification -- 4.5 Conclusion -- References -- Chapter 5 Performance Enhancements for LTE‐Connected UAVs: Experiments and Simulations -- 5.1 Introduction -- 5.2 LTE Live Network Measurements -- 5.2.1 Downlink Experiments -- 5.2.2 Path‐Loss Model Characterization -- 5.2.3 Uplink Experiments -- 5.3 Performance in LTE Networks -- 5.4 Reliability Enhancements -- 5.4.1 Interference Cancellation -- 5.4.2 Inter‐Cell Interference Control -- 5.4.3 CoMP -- 5.4.4 Antenna Beam Selection -- 5.4.5 Dual LTE Access -- 5.4.6 Dedicated Spectrum -- 5.4.7 Discussion -- 5.5 Summary and Outlook -- References -- Chapter 6 3GPP Standardization for Cellular‐Supported UAVs -- 6.1 Short Introduction to LTE and NR -- 6.1.1 LTE Physical Layer and MIMO -- 6.1.2 NR Physical Layer and MIMO -- 6.2 Drones Served by Mobile Networks -- 6.2.1 Interference Detection and Mitigation -- 6.2.2 Mobility for Drones -- 6.2.3 Need for Drone Identification and Authorization | |
| 505 | 8 | |a 6.3 3GPP Standardization Support for UAVs -- 6.3.1 Measurement Reporting Based on RSRP Level of Multiple Cells -- 6.3.2 Height, Speed, and Location Reporting -- 6.3.3 Uplink Power Control Enhancement -- 6.3.4 Flight Path Signalling -- 6.3.5 Drone Authorization and Identification -- 6.4 Flying Mode Detection in Cellular Networks -- References -- Chapter 7 Enhanced Cellular Support for UAVs with Massive MIMO -- 7.1 Introduction -- 7.2 System Model -- 7.2.1 Cellular Network Topology -- 7.2.2 System Model -- 7.2.3 Massive MIMO Channel Estimation -- 7.2.4 Massive MIMO Spatial Multiplexing -- 7.3 Single‐User Downlink Performance -- 7.3.1 UAV Downlink C& -- C Channel -- 7.4 Massive MIMO Downlink Performance -- 7.4.1 UAV Downlink C& -- C Channel -- 7.4.2 UAV-GUE Downlink Interplay -- 7.5 Enhanced Downlink Performance -- 7.5.1 UAV Downlink C& -- C Channel -- 7.5.2 UAV-GUE Downlink Interplay -- 7.6 Uplink Performance -- 7.6.1 UAV Uplink C& -- C Channel and Data Streaming -- 7.6.2 UAV-GUE Uplink Interplay -- 7.7 Conclusions -- References -- Chapter 8 High‐Capacity Millimeter Wave UAV Communications -- 8.1 Motivation -- 8.2 UAV Roles and Use Cases Enabled by Millimeter Wave Communication -- 8.2.1 UAV Roles in Cellular Networks -- 8.2.2 UAV Use Cases Enabled by High‐Capacity Cellular Networks -- 8.3 Aerial Channel Models at Millimeter Wave Frequencies -- 8.3.1 Propagation Considerations for Aerial Channels -- 8.3.1.1 Atmospheric Considerations -- 8.3.1.2 Blockages -- 8.3.2 Air‐to‐Air Millimeter Wave Channel Model -- 8.3.3 Air‐to‐Ground Millimeter Wave Channel Model -- 8.3.4 Ray Tracing as a Tool to Obtain Channel Measurements -- 8.4 Key Aspects of UAV MIMO Communication at mmWave Frequencies -- 8.5 Establishing Aerial mmWave MIMO Links -- 8.5.1 Beam Training and Tracking for UAV Millimeter Wave Communication | |
| 505 | 8 | |a 8.5.2 Channel Estimation and Tracking in Aerial Environments -- 8.5.3 Design of Hybrid Precoders and Combiners -- 8.6 Research Opportunities -- 8.6.1 Sensing at the Tower -- 8.6.2 Joint Communication and Radar -- 8.6.3 Positioning and Mapping -- 8.7 Conclusions -- References -- Part III UAV‐Assisted Wireless Communications -- Chapter 9 Stochastic Geometry‐Based Performance Analysis of Drone Cellular Networks -- 9.1 Introduction -- 9.2 Overview of the System Model -- 9.2.1 Spatial Model -- 9.2.2 3GPP‐Inspired Mobility Model -- 9.2.3 Channel Model -- 9.2.4 Metrics of Interest -- 9.3 Average Rate -- 9.4 Handover Probability -- 9.5 Results and Discussion -- 9.5.1 Density of Interfering DBSs -- 9.5.2 Average Rate -- 9.5.3 Handover Probability -- 9.6 Conclusion -- Acknowledgment -- References -- Chapter 10 UAV Placement and Aerial-Ground Interference Coordination -- 10.1 Introduction -- 10.2 Literature Review -- 10.3 UABS Use Case for AG‐HetNets -- 10.4 UABS Placement in AG‐HetNet -- 10.5 AG‐HetNet Design Guidelines -- 10.5.1 Path‐Loss Model -- 10.5.1.1 Log‐Distance Path‐Loss Model -- 10.5.1.2 Okumura-Hata Path‐Loss Model -- 10.6 Inter‐Cell Interference Coordination -- 10.6.1 UE Association and Scheduling -- 10.7 Simulation Results -- 10.7.1 5pSE with UABSs Deployed on Hexagonal Grid -- 10.7.1.1 5pSE with Log‐Normal Path‐Loss Model -- 10.7.1.2 5pSE with Okumura-Hata Path‐Loss Model -- 10.7.2 5pSE with GA‐Based UABS Deployment Optimization -- 10.7.2.1 5pSE with Log‐Normal Path‐Loss Model -- 10.7.2.2 5pSE with Okumura-Hata Path‐Loss model -- 10.7.3 Performance Comparison Between Fixed (Hexagonal) and Optimized UABS Deployment with eICIC and FeICIC -- 10.7.3.1 Influence of LDPLM on 5pSE -- 10.7.3.2 Influence of OHPLM on 5pSE -- 10.7.4 Comparison of Computation Time for Different UABS Deployment Algorithms -- 10.8 Concluding remarks -- References | |
| 505 | 8 | |a Chapter 11 Joint Trajectory and Resource Optimization | |
| 700 | 1 | |a Zeng, Yong |4 edt | |
| 700 | 1 | |a Guvenc, Ismail |4 edt | |
| 700 | 1 | |a Zhang, Rui |4 edt | |
| 700 | 1 | |a Geraci, Giovanni |4 edt | |
| 700 | 1 | |a Matolak, David W. |4 edt | |
| 776 | 0 | 8 | |i Erscheint auch als |a Zeng, Yong |t UAV Communications for 5G and Beyond |d Newark : John Wiley & Sons, Incorporated,c2020 |n Druck-Ausgabe, Hardcover |z 978-1-119-57569-6 |
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Datensatz im Suchindex
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| author2 | Zeng, Yong Guvenc, Ismail Zhang, Rui Geraci, Giovanni Matolak, David W. |
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| author_facet | Zeng, Yong Guvenc, Ismail Zhang, Rui Geraci, Giovanni Matolak, David W. |
| building | Verbundindex |
| bvnumber | BV047442507 |
| classification_tum | ELT 620 VER 593 |
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| contents | Cover -- Title Page -- Copyright -- Contents -- List of Contributors -- Acronyms -- Part I Fundamentals of UAV Communications -- Chapter 1 Overview -- 1.1 UAV Definitions, Classes, and Global Trend -- 1.2 UAV Communication and Spectrum Requirement -- 1.3 Potential Existing Technologies for UAV Communications -- 1.3.1 Direct Link -- 1.3.2 Satellite -- 1.3.3 Ad‐Hoc Network -- 1.3.4 Cellular Network -- 1.4 Two Paradigms in Cellular UAV Communications -- 1.4.1 Cellular‐Connected UAVs -- 1.4.2 UAV‐Assisted Wireless Communications -- 1.5 New Opportunities and Challenges -- 1.5.1 High Altitude -- 1.5.2 High LoS Probability -- 1.5.3 High 3D Mobility -- 1.5.4 SWAP Constraints -- 1.6 Chapter Summary and Main Organization of the Book -- References -- Chapter 2 A Survey of Air‐to‐Ground Propagation Channel Modeling for Unmanned Aerial Vehicles -- 2.1 Introduction -- 2.2 Literature Review -- 2.2.1 Literature Review on Aerial Propagation -- 2.2.2 Existing Surveys on UAV AG Propagation -- 2.3 UAV AG Propagation Characteristics -- 2.3.1 Comparison of UAV AG and Terrestrial Propagation -- 2.3.2 Frequency Bands for UAV AG Propagation -- 2.3.3 Scattering Characteristics for AG Propagation -- 2.3.4 Antenna Configurations for AG Propagation -- 2.3.5 Doppler Effects -- 2.4 AG Channel Measurements: Configurations, Challenges, Scenarios, and Waveforms -- 2.4.1 Channel Measurement Configurations -- 2.4.2 Challenges in AG Channel Measurements -- 2.4.3 AG Propagation Scenarios -- 2.4.3.1 Open Space -- 2.4.3.2 Hilly/Mountainous -- 2.4.3.3 Forest -- 2.4.3.4 Water/Sea -- 2.4.4 Elevation Angle Effects -- 2.5 UAV AG Propagation Measurement and Simulation Results in the Literature -- 2.5.1 Path Loss/Shadowing -- 2.5.2 Delay Dispersion -- 2.5.3 Narrowband Fading and Ricean K‐factor -- 2.5.4 Doppler Spread -- 2.5.5 Effects of UAV AG Measurement Environment 2.5.5.1 Urban/Suburban -- 2.5.5.2 Rural/Open Field -- 2.5.5.3 Mountains/Hilly, Over Sea, Forest -- 2.5.6 Simulations for Channel Characterization -- 2.6 UAV AG Propagation Models -- 2.6.1 AG Propagation Channel Model Types -- 2.6.2 Path‐Loss and Large‐Scale Fading Models -- 2.6.2.1 Free‐Space Path‐Loss Model -- 2.6.2.2 Floating‐Intercept Path‐Loss Model -- 2.6.2.3 Dual‐Slope Path‐Loss Model -- 2.6.2.4 Log‐Distance Path‐Loss Model -- 2.6.2.5 Modified FSPL Model -- 2.6.2.6 Two‐Ray PL Model -- 2.6.2.7 Log‐Distance FI Model -- 2.6.2.8 LOS/NLOS Mixture Path‐Loss Model -- 2.6.3 Airframe Shadowing -- 2.6.4 Small‐Scale Fading Models -- 2.6.5 Intermittent MPCs -- 2.6.6 Effect of Frequency Bands on Channel Models -- 2.6.7 MIMO AG Propagation Channel Models -- 2.6.8 Comparison of Different AG Channel Models -- 2.6.8.1 Large‐Scale Fading Models -- 2.6.8.2 Small‐Scale Fading Models -- 2.6.9 Comparison of Traditional Channel Models with UAV AG Propagation Channel Models -- 2.6.10 Ray Tracing Simulations -- 2.6.11 3GPP Channel Models for UAVs -- 2.7 Conclusions -- References -- Chapter 3 UAV Detection and Identification -- 3.1 Introduction -- 3.2 RF‐Based UAV Detection Techniques -- 3.2.1 RF Fingerprinting Technique -- 3.2.2 WiFi Fingerprinting Technique -- 3.3 Multistage UAV RF Signal Detection -- 3.3.1 Preprocessing Step: Multiresolution Analysis -- 3.3.2 The Naive Bayesian Decision Mechanism for RF Signal Detection -- 3.3.3 Detection of WiFi and Bluetooth Interference -- 3.4 UAV Classification Using RF Fingerprints -- 3.4.1 Feature Selection Using Neighborhood Components Analysis (NCA) -- 3.5 Experimental Results -- 3.5.1 Experimental Setup -- 3.5.2 Detection Results -- 3.5.3 UAV Classification Results -- 3.6 Conclusion -- Acknowledgments -- References -- Part II Cellular‐Connected UAV Communications -- Chapter 4 Performance Analysis for Cellular‐Connected UAVs 4.1 Introduction -- 4.1.1 Motivation -- 4.1.2 Related Works -- 4.1.3 Contributions and Chapter Structure -- 4.2 Modelling Preliminaries -- 4.2.1 Stochastic Geometry -- 4.2.2 Network Architecture -- 4.2.3 Channel Model -- 4.2.4 Blockage Modeling and LoS Probability -- 4.2.5 User Association Strategy and Link SINR -- 4.3 Performance Analysis -- 4.3.1 Exact Coverage Probability -- 4.3.2 Approximations for UAV Coverage Probability -- 4.3.2.1 Discarding NLoS and Noise Effects -- 4.3.2.2 Moment Matching -- 4.3.3 Achievable Throughput and Area Spectral Efficiency Analysis -- 4.4 System Design: Study Cases and Discussion -- 4.4.1 Analysis of Accuracy -- 4.4.2 Design Parameters -- 4.4.2.1 Impact of UAV Altitude -- 4.4.2.2 Impact of UAV Antenna Beamwidth -- 4.4.2.3 Impact of UAV Antenna Tilt -- 4.4.2.4 Impact of Different Types of Environment -- 4.4.3 Heterogeneous Networks - Tier Selection -- 4.4.4 Network Densification -- 4.5 Conclusion -- References -- Chapter 5 Performance Enhancements for LTE‐Connected UAVs: Experiments and Simulations -- 5.1 Introduction -- 5.2 LTE Live Network Measurements -- 5.2.1 Downlink Experiments -- 5.2.2 Path‐Loss Model Characterization -- 5.2.3 Uplink Experiments -- 5.3 Performance in LTE Networks -- 5.4 Reliability Enhancements -- 5.4.1 Interference Cancellation -- 5.4.2 Inter‐Cell Interference Control -- 5.4.3 CoMP -- 5.4.4 Antenna Beam Selection -- 5.4.5 Dual LTE Access -- 5.4.6 Dedicated Spectrum -- 5.4.7 Discussion -- 5.5 Summary and Outlook -- References -- Chapter 6 3GPP Standardization for Cellular‐Supported UAVs -- 6.1 Short Introduction to LTE and NR -- 6.1.1 LTE Physical Layer and MIMO -- 6.1.2 NR Physical Layer and MIMO -- 6.2 Drones Served by Mobile Networks -- 6.2.1 Interference Detection and Mitigation -- 6.2.2 Mobility for Drones -- 6.2.3 Need for Drone Identification and Authorization 6.3 3GPP Standardization Support for UAVs -- 6.3.1 Measurement Reporting Based on RSRP Level of Multiple Cells -- 6.3.2 Height, Speed, and Location Reporting -- 6.3.3 Uplink Power Control Enhancement -- 6.3.4 Flight Path Signalling -- 6.3.5 Drone Authorization and Identification -- 6.4 Flying Mode Detection in Cellular Networks -- References -- Chapter 7 Enhanced Cellular Support for UAVs with Massive MIMO -- 7.1 Introduction -- 7.2 System Model -- 7.2.1 Cellular Network Topology -- 7.2.2 System Model -- 7.2.3 Massive MIMO Channel Estimation -- 7.2.4 Massive MIMO Spatial Multiplexing -- 7.3 Single‐User Downlink Performance -- 7.3.1 UAV Downlink C& -- C Channel -- 7.4 Massive MIMO Downlink Performance -- 7.4.1 UAV Downlink C& -- C Channel -- 7.4.2 UAV-GUE Downlink Interplay -- 7.5 Enhanced Downlink Performance -- 7.5.1 UAV Downlink C& -- C Channel -- 7.5.2 UAV-GUE Downlink Interplay -- 7.6 Uplink Performance -- 7.6.1 UAV Uplink C& -- C Channel and Data Streaming -- 7.6.2 UAV-GUE Uplink Interplay -- 7.7 Conclusions -- References -- Chapter 8 High‐Capacity Millimeter Wave UAV Communications -- 8.1 Motivation -- 8.2 UAV Roles and Use Cases Enabled by Millimeter Wave Communication -- 8.2.1 UAV Roles in Cellular Networks -- 8.2.2 UAV Use Cases Enabled by High‐Capacity Cellular Networks -- 8.3 Aerial Channel Models at Millimeter Wave Frequencies -- 8.3.1 Propagation Considerations for Aerial Channels -- 8.3.1.1 Atmospheric Considerations -- 8.3.1.2 Blockages -- 8.3.2 Air‐to‐Air Millimeter Wave Channel Model -- 8.3.3 Air‐to‐Ground Millimeter Wave Channel Model -- 8.3.4 Ray Tracing as a Tool to Obtain Channel Measurements -- 8.4 Key Aspects of UAV MIMO Communication at mmWave Frequencies -- 8.5 Establishing Aerial mmWave MIMO Links -- 8.5.1 Beam Training and Tracking for UAV Millimeter Wave Communication 8.5.2 Channel Estimation and Tracking in Aerial Environments -- 8.5.3 Design of Hybrid Precoders and Combiners -- 8.6 Research Opportunities -- 8.6.1 Sensing at the Tower -- 8.6.2 Joint Communication and Radar -- 8.6.3 Positioning and Mapping -- 8.7 Conclusions -- References -- Part III UAV‐Assisted Wireless Communications -- Chapter 9 Stochastic Geometry‐Based Performance Analysis of Drone Cellular Networks -- 9.1 Introduction -- 9.2 Overview of the System Model -- 9.2.1 Spatial Model -- 9.2.2 3GPP‐Inspired Mobility Model -- 9.2.3 Channel Model -- 9.2.4 Metrics of Interest -- 9.3 Average Rate -- 9.4 Handover Probability -- 9.5 Results and Discussion -- 9.5.1 Density of Interfering DBSs -- 9.5.2 Average Rate -- 9.5.3 Handover Probability -- 9.6 Conclusion -- Acknowledgment -- References -- Chapter 10 UAV Placement and Aerial-Ground Interference Coordination -- 10.1 Introduction -- 10.2 Literature Review -- 10.3 UABS Use Case for AG‐HetNets -- 10.4 UABS Placement in AG‐HetNet -- 10.5 AG‐HetNet Design Guidelines -- 10.5.1 Path‐Loss Model -- 10.5.1.1 Log‐Distance Path‐Loss Model -- 10.5.1.2 Okumura-Hata Path‐Loss Model -- 10.6 Inter‐Cell Interference Coordination -- 10.6.1 UE Association and Scheduling -- 10.7 Simulation Results -- 10.7.1 5pSE with UABSs Deployed on Hexagonal Grid -- 10.7.1.1 5pSE with Log‐Normal Path‐Loss Model -- 10.7.1.2 5pSE with Okumura-Hata Path‐Loss Model -- 10.7.2 5pSE with GA‐Based UABS Deployment Optimization -- 10.7.2.1 5pSE with Log‐Normal Path‐Loss Model -- 10.7.2.2 5pSE with Okumura-Hata Path‐Loss model -- 10.7.3 Performance Comparison Between Fixed (Hexagonal) and Optimized UABS Deployment with eICIC and FeICIC -- 10.7.3.1 Influence of LDPLM on 5pSE -- 10.7.3.2 Influence of OHPLM on 5pSE -- 10.7.4 Comparison of Computation Time for Different UABS Deployment Algorithms -- 10.8 Concluding remarks -- References Chapter 11 Joint Trajectory and Resource Optimization |
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| discipline | Elektrotechnik Verkehrstechnik Verkehr / Transport |
| discipline_str_mv | Elektrotechnik Verkehrstechnik Verkehr / Transport |
| format | Electronic eBook |
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Matolak</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">Hoboken, NJ</subfield><subfield code="b">Wiley</subfield><subfield code="c">2021</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">[Piscataway Township, New Jersey, USA]</subfield><subfield code="b">IEEE Press</subfield></datafield><datafield tag="264" ind1=" " ind2="4"><subfield code="c">© 2021</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">1 Online-Ressource (xxiv, 440 Seiten)</subfield><subfield code="b">Illustrationen, Diagramme</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="b">c</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="b">cr</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">Description based on publisher supplied metadata and other sources</subfield></datafield><datafield tag="505" ind1="8" ind2=" "><subfield code="a">Cover -- Title Page -- Copyright -- Contents -- List of Contributors -- Acronyms -- Part I Fundamentals of UAV Communications -- Chapter 1 Overview -- 1.1 UAV Definitions, Classes, and Global Trend -- 1.2 UAV Communication and Spectrum Requirement -- 1.3 Potential Existing Technologies for UAV Communications -- 1.3.1 Direct Link -- 1.3.2 Satellite -- 1.3.3 Ad‐Hoc Network -- 1.3.4 Cellular Network -- 1.4 Two Paradigms in Cellular UAV Communications -- 1.4.1 Cellular‐Connected UAVs -- 1.4.2 UAV‐Assisted Wireless Communications -- 1.5 New Opportunities and Challenges -- 1.5.1 High Altitude -- 1.5.2 High LoS Probability -- 1.5.3 High 3D Mobility -- 1.5.4 SWAP Constraints -- 1.6 Chapter Summary and Main Organization of the Book -- References -- Chapter 2 A Survey of Air‐to‐Ground Propagation Channel Modeling for Unmanned Aerial Vehicles -- 2.1 Introduction -- 2.2 Literature Review -- 2.2.1 Literature Review on Aerial Propagation -- 2.2.2 Existing Surveys on UAV AG Propagation -- 2.3 UAV AG Propagation Characteristics -- 2.3.1 Comparison of UAV AG and Terrestrial Propagation -- 2.3.2 Frequency Bands for UAV AG Propagation -- 2.3.3 Scattering Characteristics for AG Propagation -- 2.3.4 Antenna Configurations for AG Propagation -- 2.3.5 Doppler Effects -- 2.4 AG Channel Measurements: Configurations, Challenges, Scenarios, and Waveforms -- 2.4.1 Channel Measurement Configurations -- 2.4.2 Challenges in AG Channel Measurements -- 2.4.3 AG Propagation Scenarios -- 2.4.3.1 Open Space -- 2.4.3.2 Hilly/Mountainous -- 2.4.3.3 Forest -- 2.4.3.4 Water/Sea -- 2.4.4 Elevation Angle Effects -- 2.5 UAV AG Propagation Measurement and Simulation Results in the Literature -- 2.5.1 Path Loss/Shadowing -- 2.5.2 Delay Dispersion -- 2.5.3 Narrowband Fading and Ricean K‐factor -- 2.5.4 Doppler Spread -- 2.5.5 Effects of UAV AG Measurement Environment</subfield></datafield><datafield tag="505" ind1="8" ind2=" "><subfield code="a">2.5.5.1 Urban/Suburban -- 2.5.5.2 Rural/Open Field -- 2.5.5.3 Mountains/Hilly, Over Sea, Forest -- 2.5.6 Simulations for Channel Characterization -- 2.6 UAV AG Propagation Models -- 2.6.1 AG Propagation Channel Model Types -- 2.6.2 Path‐Loss and Large‐Scale Fading Models -- 2.6.2.1 Free‐Space Path‐Loss Model -- 2.6.2.2 Floating‐Intercept Path‐Loss Model -- 2.6.2.3 Dual‐Slope Path‐Loss Model -- 2.6.2.4 Log‐Distance Path‐Loss Model -- 2.6.2.5 Modified FSPL Model -- 2.6.2.6 Two‐Ray PL Model -- 2.6.2.7 Log‐Distance FI Model -- 2.6.2.8 LOS/NLOS Mixture Path‐Loss Model -- 2.6.3 Airframe Shadowing -- 2.6.4 Small‐Scale Fading Models -- 2.6.5 Intermittent MPCs -- 2.6.6 Effect of Frequency Bands on Channel Models -- 2.6.7 MIMO AG Propagation Channel Models -- 2.6.8 Comparison of Different AG Channel Models -- 2.6.8.1 Large‐Scale Fading Models -- 2.6.8.2 Small‐Scale Fading Models -- 2.6.9 Comparison of Traditional Channel Models with UAV AG Propagation Channel Models -- 2.6.10 Ray Tracing Simulations -- 2.6.11 3GPP Channel Models for UAVs -- 2.7 Conclusions -- References -- Chapter 3 UAV Detection and Identification -- 3.1 Introduction -- 3.2 RF‐Based UAV Detection Techniques -- 3.2.1 RF Fingerprinting Technique -- 3.2.2 WiFi Fingerprinting Technique -- 3.3 Multistage UAV RF Signal Detection -- 3.3.1 Preprocessing Step: Multiresolution Analysis -- 3.3.2 The Naive Bayesian Decision Mechanism for RF Signal Detection -- 3.3.3 Detection of WiFi and Bluetooth Interference -- 3.4 UAV Classification Using RF Fingerprints -- 3.4.1 Feature Selection Using Neighborhood Components Analysis (NCA) -- 3.5 Experimental Results -- 3.5.1 Experimental Setup -- 3.5.2 Detection Results -- 3.5.3 UAV Classification Results -- 3.6 Conclusion -- Acknowledgments -- References -- Part II Cellular‐Connected UAV Communications -- Chapter 4 Performance Analysis for Cellular‐Connected UAVs</subfield></datafield><datafield tag="505" ind1="8" ind2=" "><subfield code="a">4.1 Introduction -- 4.1.1 Motivation -- 4.1.2 Related Works -- 4.1.3 Contributions and Chapter Structure -- 4.2 Modelling Preliminaries -- 4.2.1 Stochastic Geometry -- 4.2.2 Network Architecture -- 4.2.3 Channel Model -- 4.2.4 Blockage Modeling and LoS Probability -- 4.2.5 User Association Strategy and Link SINR -- 4.3 Performance Analysis -- 4.3.1 Exact Coverage Probability -- 4.3.2 Approximations for UAV Coverage Probability -- 4.3.2.1 Discarding NLoS and Noise Effects -- 4.3.2.2 Moment Matching -- 4.3.3 Achievable Throughput and Area Spectral Efficiency Analysis -- 4.4 System Design: Study Cases and Discussion -- 4.4.1 Analysis of Accuracy -- 4.4.2 Design Parameters -- 4.4.2.1 Impact of UAV Altitude -- 4.4.2.2 Impact of UAV Antenna Beamwidth -- 4.4.2.3 Impact of UAV Antenna Tilt -- 4.4.2.4 Impact of Different Types of Environment -- 4.4.3 Heterogeneous Networks - Tier Selection -- 4.4.4 Network Densification -- 4.5 Conclusion -- References -- Chapter 5 Performance Enhancements for LTE‐Connected UAVs: Experiments and Simulations -- 5.1 Introduction -- 5.2 LTE Live Network Measurements -- 5.2.1 Downlink Experiments -- 5.2.2 Path‐Loss Model Characterization -- 5.2.3 Uplink Experiments -- 5.3 Performance in LTE Networks -- 5.4 Reliability Enhancements -- 5.4.1 Interference Cancellation -- 5.4.2 Inter‐Cell Interference Control -- 5.4.3 CoMP -- 5.4.4 Antenna Beam Selection -- 5.4.5 Dual LTE Access -- 5.4.6 Dedicated Spectrum -- 5.4.7 Discussion -- 5.5 Summary and Outlook -- References -- Chapter 6 3GPP Standardization for Cellular‐Supported UAVs -- 6.1 Short Introduction to LTE and NR -- 6.1.1 LTE Physical Layer and MIMO -- 6.1.2 NR Physical Layer and MIMO -- 6.2 Drones Served by Mobile Networks -- 6.2.1 Interference Detection and Mitigation -- 6.2.2 Mobility for Drones -- 6.2.3 Need for Drone Identification and Authorization</subfield></datafield><datafield tag="505" ind1="8" ind2=" "><subfield code="a">6.3 3GPP Standardization Support for UAVs -- 6.3.1 Measurement Reporting Based on RSRP Level of Multiple Cells -- 6.3.2 Height, Speed, and Location Reporting -- 6.3.3 Uplink Power Control Enhancement -- 6.3.4 Flight Path Signalling -- 6.3.5 Drone Authorization and Identification -- 6.4 Flying Mode Detection in Cellular Networks -- References -- Chapter 7 Enhanced Cellular Support for UAVs with Massive MIMO -- 7.1 Introduction -- 7.2 System Model -- 7.2.1 Cellular Network Topology -- 7.2.2 System Model -- 7.2.3 Massive MIMO Channel Estimation -- 7.2.4 Massive MIMO Spatial Multiplexing -- 7.3 Single‐User Downlink Performance -- 7.3.1 UAV Downlink C&amp -- C Channel -- 7.4 Massive MIMO Downlink Performance -- 7.4.1 UAV Downlink C&amp -- C Channel -- 7.4.2 UAV-GUE Downlink Interplay -- 7.5 Enhanced Downlink Performance -- 7.5.1 UAV Downlink C&amp -- C Channel -- 7.5.2 UAV-GUE Downlink Interplay -- 7.6 Uplink Performance -- 7.6.1 UAV Uplink C&amp -- C Channel and Data Streaming -- 7.6.2 UAV-GUE Uplink Interplay -- 7.7 Conclusions -- References -- Chapter 8 High‐Capacity Millimeter Wave UAV Communications -- 8.1 Motivation -- 8.2 UAV Roles and Use Cases Enabled by Millimeter Wave Communication -- 8.2.1 UAV Roles in Cellular Networks -- 8.2.2 UAV Use Cases Enabled by High‐Capacity Cellular Networks -- 8.3 Aerial Channel Models at Millimeter Wave Frequencies -- 8.3.1 Propagation Considerations for Aerial Channels -- 8.3.1.1 Atmospheric Considerations -- 8.3.1.2 Blockages -- 8.3.2 Air‐to‐Air Millimeter Wave Channel Model -- 8.3.3 Air‐to‐Ground Millimeter Wave Channel Model -- 8.3.4 Ray Tracing as a Tool to Obtain Channel Measurements -- 8.4 Key Aspects of UAV MIMO Communication at mmWave Frequencies -- 8.5 Establishing Aerial mmWave MIMO Links -- 8.5.1 Beam Training and Tracking for UAV Millimeter Wave Communication</subfield></datafield><datafield tag="505" ind1="8" ind2=" "><subfield code="a">8.5.2 Channel Estimation and Tracking in Aerial Environments -- 8.5.3 Design of Hybrid Precoders and Combiners -- 8.6 Research Opportunities -- 8.6.1 Sensing at the Tower -- 8.6.2 Joint Communication and Radar -- 8.6.3 Positioning and Mapping -- 8.7 Conclusions -- References -- Part III UAV‐Assisted Wireless Communications -- Chapter 9 Stochastic Geometry‐Based Performance Analysis of Drone Cellular Networks -- 9.1 Introduction -- 9.2 Overview of the System Model -- 9.2.1 Spatial Model -- 9.2.2 3GPP‐Inspired Mobility Model -- 9.2.3 Channel Model -- 9.2.4 Metrics of Interest -- 9.3 Average Rate -- 9.4 Handover Probability -- 9.5 Results and Discussion -- 9.5.1 Density of Interfering DBSs -- 9.5.2 Average Rate -- 9.5.3 Handover Probability -- 9.6 Conclusion -- Acknowledgment -- References -- Chapter 10 UAV Placement and Aerial-Ground Interference Coordination -- 10.1 Introduction -- 10.2 Literature Review -- 10.3 UABS Use Case for AG‐HetNets -- 10.4 UABS Placement in AG‐HetNet -- 10.5 AG‐HetNet Design Guidelines -- 10.5.1 Path‐Loss Model -- 10.5.1.1 Log‐Distance Path‐Loss Model -- 10.5.1.2 Okumura-Hata Path‐Loss Model -- 10.6 Inter‐Cell Interference Coordination -- 10.6.1 UE Association and Scheduling -- 10.7 Simulation Results -- 10.7.1 5pSE with UABSs Deployed on Hexagonal Grid -- 10.7.1.1 5pSE with Log‐Normal Path‐Loss Model -- 10.7.1.2 5pSE with Okumura-Hata Path‐Loss Model -- 10.7.2 5pSE with GA‐Based UABS Deployment Optimization -- 10.7.2.1 5pSE with Log‐Normal Path‐Loss Model -- 10.7.2.2 5pSE with Okumura-Hata Path‐Loss model -- 10.7.3 Performance Comparison Between Fixed (Hexagonal) and Optimized UABS Deployment with eICIC and FeICIC -- 10.7.3.1 Influence of LDPLM on 5pSE -- 10.7.3.2 Influence of OHPLM on 5pSE -- 10.7.4 Comparison of Computation Time for Different UABS Deployment Algorithms -- 10.8 Concluding remarks -- References</subfield></datafield><datafield tag="505" ind1="8" ind2=" "><subfield code="a">Chapter 11 Joint Trajectory and Resource Optimization</subfield></datafield><datafield 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| id | DE-604.BV047442507 |
| illustrated | Not Illustrated |
| index_date | 2024-07-03T18:01:24Z |
| indexdate | 2024-07-10T09:12:16Z |
| institution | BVB |
| isbn | 9781119575672 9781119575726 9781119575795 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-032844659 |
| oclc_num | 1227389882 |
| open_access_boolean | |
| owner | DE-91 DE-BY-TUM DE-573 |
| owner_facet | DE-91 DE-BY-TUM DE-573 |
| physical | 1 Online-Ressource (xxiv, 440 Seiten) Illustrationen, Diagramme |
| psigel | ZDB-30-PQE ZDB-35-WEL ZDB-30-PQE TUM_PDA_PQE_Kauf |
| publishDate | 2021 |
| publishDateSearch | 2021 |
| publishDateSort | 2021 |
| publisher | Wiley IEEE Press |
| record_format | marc |
| spelling | UAV communications for 5G and beyond edited by Yong Zeng, Ismail Guvenc, Rui Zhang, Giovanni Geraci, David W. Matolak Hoboken, NJ Wiley 2021 [Piscataway Township, New Jersey, USA] IEEE Press © 2021 1 Online-Ressource (xxiv, 440 Seiten) Illustrationen, Diagramme txt rdacontent c rdamedia cr rdacarrier Description based on publisher supplied metadata and other sources Cover -- Title Page -- Copyright -- Contents -- List of Contributors -- Acronyms -- Part I Fundamentals of UAV Communications -- Chapter 1 Overview -- 1.1 UAV Definitions, Classes, and Global Trend -- 1.2 UAV Communication and Spectrum Requirement -- 1.3 Potential Existing Technologies for UAV Communications -- 1.3.1 Direct Link -- 1.3.2 Satellite -- 1.3.3 Ad‐Hoc Network -- 1.3.4 Cellular Network -- 1.4 Two Paradigms in Cellular UAV Communications -- 1.4.1 Cellular‐Connected UAVs -- 1.4.2 UAV‐Assisted Wireless Communications -- 1.5 New Opportunities and Challenges -- 1.5.1 High Altitude -- 1.5.2 High LoS Probability -- 1.5.3 High 3D Mobility -- 1.5.4 SWAP Constraints -- 1.6 Chapter Summary and Main Organization of the Book -- References -- Chapter 2 A Survey of Air‐to‐Ground Propagation Channel Modeling for Unmanned Aerial Vehicles -- 2.1 Introduction -- 2.2 Literature Review -- 2.2.1 Literature Review on Aerial Propagation -- 2.2.2 Existing Surveys on UAV AG Propagation -- 2.3 UAV AG Propagation Characteristics -- 2.3.1 Comparison of UAV AG and Terrestrial Propagation -- 2.3.2 Frequency Bands for UAV AG Propagation -- 2.3.3 Scattering Characteristics for AG Propagation -- 2.3.4 Antenna Configurations for AG Propagation -- 2.3.5 Doppler Effects -- 2.4 AG Channel Measurements: Configurations, Challenges, Scenarios, and Waveforms -- 2.4.1 Channel Measurement Configurations -- 2.4.2 Challenges in AG Channel Measurements -- 2.4.3 AG Propagation Scenarios -- 2.4.3.1 Open Space -- 2.4.3.2 Hilly/Mountainous -- 2.4.3.3 Forest -- 2.4.3.4 Water/Sea -- 2.4.4 Elevation Angle Effects -- 2.5 UAV AG Propagation Measurement and Simulation Results in the Literature -- 2.5.1 Path Loss/Shadowing -- 2.5.2 Delay Dispersion -- 2.5.3 Narrowband Fading and Ricean K‐factor -- 2.5.4 Doppler Spread -- 2.5.5 Effects of UAV AG Measurement Environment 2.5.5.1 Urban/Suburban -- 2.5.5.2 Rural/Open Field -- 2.5.5.3 Mountains/Hilly, Over Sea, Forest -- 2.5.6 Simulations for Channel Characterization -- 2.6 UAV AG Propagation Models -- 2.6.1 AG Propagation Channel Model Types -- 2.6.2 Path‐Loss and Large‐Scale Fading Models -- 2.6.2.1 Free‐Space Path‐Loss Model -- 2.6.2.2 Floating‐Intercept Path‐Loss Model -- 2.6.2.3 Dual‐Slope Path‐Loss Model -- 2.6.2.4 Log‐Distance Path‐Loss Model -- 2.6.2.5 Modified FSPL Model -- 2.6.2.6 Two‐Ray PL Model -- 2.6.2.7 Log‐Distance FI Model -- 2.6.2.8 LOS/NLOS Mixture Path‐Loss Model -- 2.6.3 Airframe Shadowing -- 2.6.4 Small‐Scale Fading Models -- 2.6.5 Intermittent MPCs -- 2.6.6 Effect of Frequency Bands on Channel Models -- 2.6.7 MIMO AG Propagation Channel Models -- 2.6.8 Comparison of Different AG Channel Models -- 2.6.8.1 Large‐Scale Fading Models -- 2.6.8.2 Small‐Scale Fading Models -- 2.6.9 Comparison of Traditional Channel Models with UAV AG Propagation Channel Models -- 2.6.10 Ray Tracing Simulations -- 2.6.11 3GPP Channel Models for UAVs -- 2.7 Conclusions -- References -- Chapter 3 UAV Detection and Identification -- 3.1 Introduction -- 3.2 RF‐Based UAV Detection Techniques -- 3.2.1 RF Fingerprinting Technique -- 3.2.2 WiFi Fingerprinting Technique -- 3.3 Multistage UAV RF Signal Detection -- 3.3.1 Preprocessing Step: Multiresolution Analysis -- 3.3.2 The Naive Bayesian Decision Mechanism for RF Signal Detection -- 3.3.3 Detection of WiFi and Bluetooth Interference -- 3.4 UAV Classification Using RF Fingerprints -- 3.4.1 Feature Selection Using Neighborhood Components Analysis (NCA) -- 3.5 Experimental Results -- 3.5.1 Experimental Setup -- 3.5.2 Detection Results -- 3.5.3 UAV Classification Results -- 3.6 Conclusion -- Acknowledgments -- References -- Part II Cellular‐Connected UAV Communications -- Chapter 4 Performance Analysis for Cellular‐Connected UAVs 4.1 Introduction -- 4.1.1 Motivation -- 4.1.2 Related Works -- 4.1.3 Contributions and Chapter Structure -- 4.2 Modelling Preliminaries -- 4.2.1 Stochastic Geometry -- 4.2.2 Network Architecture -- 4.2.3 Channel Model -- 4.2.4 Blockage Modeling and LoS Probability -- 4.2.5 User Association Strategy and Link SINR -- 4.3 Performance Analysis -- 4.3.1 Exact Coverage Probability -- 4.3.2 Approximations for UAV Coverage Probability -- 4.3.2.1 Discarding NLoS and Noise Effects -- 4.3.2.2 Moment Matching -- 4.3.3 Achievable Throughput and Area Spectral Efficiency Analysis -- 4.4 System Design: Study Cases and Discussion -- 4.4.1 Analysis of Accuracy -- 4.4.2 Design Parameters -- 4.4.2.1 Impact of UAV Altitude -- 4.4.2.2 Impact of UAV Antenna Beamwidth -- 4.4.2.3 Impact of UAV Antenna Tilt -- 4.4.2.4 Impact of Different Types of Environment -- 4.4.3 Heterogeneous Networks - Tier Selection -- 4.4.4 Network Densification -- 4.5 Conclusion -- References -- Chapter 5 Performance Enhancements for LTE‐Connected UAVs: Experiments and Simulations -- 5.1 Introduction -- 5.2 LTE Live Network Measurements -- 5.2.1 Downlink Experiments -- 5.2.2 Path‐Loss Model Characterization -- 5.2.3 Uplink Experiments -- 5.3 Performance in LTE Networks -- 5.4 Reliability Enhancements -- 5.4.1 Interference Cancellation -- 5.4.2 Inter‐Cell Interference Control -- 5.4.3 CoMP -- 5.4.4 Antenna Beam Selection -- 5.4.5 Dual LTE Access -- 5.4.6 Dedicated Spectrum -- 5.4.7 Discussion -- 5.5 Summary and Outlook -- References -- Chapter 6 3GPP Standardization for Cellular‐Supported UAVs -- 6.1 Short Introduction to LTE and NR -- 6.1.1 LTE Physical Layer and MIMO -- 6.1.2 NR Physical Layer and MIMO -- 6.2 Drones Served by Mobile Networks -- 6.2.1 Interference Detection and Mitigation -- 6.2.2 Mobility for Drones -- 6.2.3 Need for Drone Identification and Authorization 6.3 3GPP Standardization Support for UAVs -- 6.3.1 Measurement Reporting Based on RSRP Level of Multiple Cells -- 6.3.2 Height, Speed, and Location Reporting -- 6.3.3 Uplink Power Control Enhancement -- 6.3.4 Flight Path Signalling -- 6.3.5 Drone Authorization and Identification -- 6.4 Flying Mode Detection in Cellular Networks -- References -- Chapter 7 Enhanced Cellular Support for UAVs with Massive MIMO -- 7.1 Introduction -- 7.2 System Model -- 7.2.1 Cellular Network Topology -- 7.2.2 System Model -- 7.2.3 Massive MIMO Channel Estimation -- 7.2.4 Massive MIMO Spatial Multiplexing -- 7.3 Single‐User Downlink Performance -- 7.3.1 UAV Downlink C& -- C Channel -- 7.4 Massive MIMO Downlink Performance -- 7.4.1 UAV Downlink C& -- C Channel -- 7.4.2 UAV-GUE Downlink Interplay -- 7.5 Enhanced Downlink Performance -- 7.5.1 UAV Downlink C& -- C Channel -- 7.5.2 UAV-GUE Downlink Interplay -- 7.6 Uplink Performance -- 7.6.1 UAV Uplink C& -- C Channel and Data Streaming -- 7.6.2 UAV-GUE Uplink Interplay -- 7.7 Conclusions -- References -- Chapter 8 High‐Capacity Millimeter Wave UAV Communications -- 8.1 Motivation -- 8.2 UAV Roles and Use Cases Enabled by Millimeter Wave Communication -- 8.2.1 UAV Roles in Cellular Networks -- 8.2.2 UAV Use Cases Enabled by High‐Capacity Cellular Networks -- 8.3 Aerial Channel Models at Millimeter Wave Frequencies -- 8.3.1 Propagation Considerations for Aerial Channels -- 8.3.1.1 Atmospheric Considerations -- 8.3.1.2 Blockages -- 8.3.2 Air‐to‐Air Millimeter Wave Channel Model -- 8.3.3 Air‐to‐Ground Millimeter Wave Channel Model -- 8.3.4 Ray Tracing as a Tool to Obtain Channel Measurements -- 8.4 Key Aspects of UAV MIMO Communication at mmWave Frequencies -- 8.5 Establishing Aerial mmWave MIMO Links -- 8.5.1 Beam Training and Tracking for UAV Millimeter Wave Communication 8.5.2 Channel Estimation and Tracking in Aerial Environments -- 8.5.3 Design of Hybrid Precoders and Combiners -- 8.6 Research Opportunities -- 8.6.1 Sensing at the Tower -- 8.6.2 Joint Communication and Radar -- 8.6.3 Positioning and Mapping -- 8.7 Conclusions -- References -- Part III UAV‐Assisted Wireless Communications -- Chapter 9 Stochastic Geometry‐Based Performance Analysis of Drone Cellular Networks -- 9.1 Introduction -- 9.2 Overview of the System Model -- 9.2.1 Spatial Model -- 9.2.2 3GPP‐Inspired Mobility Model -- 9.2.3 Channel Model -- 9.2.4 Metrics of Interest -- 9.3 Average Rate -- 9.4 Handover Probability -- 9.5 Results and Discussion -- 9.5.1 Density of Interfering DBSs -- 9.5.2 Average Rate -- 9.5.3 Handover Probability -- 9.6 Conclusion -- Acknowledgment -- References -- Chapter 10 UAV Placement and Aerial-Ground Interference Coordination -- 10.1 Introduction -- 10.2 Literature Review -- 10.3 UABS Use Case for AG‐HetNets -- 10.4 UABS Placement in AG‐HetNet -- 10.5 AG‐HetNet Design Guidelines -- 10.5.1 Path‐Loss Model -- 10.5.1.1 Log‐Distance Path‐Loss Model -- 10.5.1.2 Okumura-Hata Path‐Loss Model -- 10.6 Inter‐Cell Interference Coordination -- 10.6.1 UE Association and Scheduling -- 10.7 Simulation Results -- 10.7.1 5pSE with UABSs Deployed on Hexagonal Grid -- 10.7.1.1 5pSE with Log‐Normal Path‐Loss Model -- 10.7.1.2 5pSE with Okumura-Hata Path‐Loss Model -- 10.7.2 5pSE with GA‐Based UABS Deployment Optimization -- 10.7.2.1 5pSE with Log‐Normal Path‐Loss Model -- 10.7.2.2 5pSE with Okumura-Hata Path‐Loss model -- 10.7.3 Performance Comparison Between Fixed (Hexagonal) and Optimized UABS Deployment with eICIC and FeICIC -- 10.7.3.1 Influence of LDPLM on 5pSE -- 10.7.3.2 Influence of OHPLM on 5pSE -- 10.7.4 Comparison of Computation Time for Different UABS Deployment Algorithms -- 10.8 Concluding remarks -- References Chapter 11 Joint Trajectory and Resource Optimization Zeng, Yong edt Guvenc, Ismail edt Zhang, Rui edt Geraci, Giovanni edt Matolak, David W. edt Erscheint auch als Zeng, Yong UAV Communications for 5G and Beyond Newark : John Wiley & Sons, Incorporated,c2020 Druck-Ausgabe, Hardcover 978-1-119-57569-6 |
| spellingShingle | UAV communications for 5G and beyond Cover -- Title Page -- Copyright -- Contents -- List of Contributors -- Acronyms -- Part I Fundamentals of UAV Communications -- Chapter 1 Overview -- 1.1 UAV Definitions, Classes, and Global Trend -- 1.2 UAV Communication and Spectrum Requirement -- 1.3 Potential Existing Technologies for UAV Communications -- 1.3.1 Direct Link -- 1.3.2 Satellite -- 1.3.3 Ad‐Hoc Network -- 1.3.4 Cellular Network -- 1.4 Two Paradigms in Cellular UAV Communications -- 1.4.1 Cellular‐Connected UAVs -- 1.4.2 UAV‐Assisted Wireless Communications -- 1.5 New Opportunities and Challenges -- 1.5.1 High Altitude -- 1.5.2 High LoS Probability -- 1.5.3 High 3D Mobility -- 1.5.4 SWAP Constraints -- 1.6 Chapter Summary and Main Organization of the Book -- References -- Chapter 2 A Survey of Air‐to‐Ground Propagation Channel Modeling for Unmanned Aerial Vehicles -- 2.1 Introduction -- 2.2 Literature Review -- 2.2.1 Literature Review on Aerial Propagation -- 2.2.2 Existing Surveys on UAV AG Propagation -- 2.3 UAV AG Propagation Characteristics -- 2.3.1 Comparison of UAV AG and Terrestrial Propagation -- 2.3.2 Frequency Bands for UAV AG Propagation -- 2.3.3 Scattering Characteristics for AG Propagation -- 2.3.4 Antenna Configurations for AG Propagation -- 2.3.5 Doppler Effects -- 2.4 AG Channel Measurements: Configurations, Challenges, Scenarios, and Waveforms -- 2.4.1 Channel Measurement Configurations -- 2.4.2 Challenges in AG Channel Measurements -- 2.4.3 AG Propagation Scenarios -- 2.4.3.1 Open Space -- 2.4.3.2 Hilly/Mountainous -- 2.4.3.3 Forest -- 2.4.3.4 Water/Sea -- 2.4.4 Elevation Angle Effects -- 2.5 UAV AG Propagation Measurement and Simulation Results in the Literature -- 2.5.1 Path Loss/Shadowing -- 2.5.2 Delay Dispersion -- 2.5.3 Narrowband Fading and Ricean K‐factor -- 2.5.4 Doppler Spread -- 2.5.5 Effects of UAV AG Measurement Environment 2.5.5.1 Urban/Suburban -- 2.5.5.2 Rural/Open Field -- 2.5.5.3 Mountains/Hilly, Over Sea, Forest -- 2.5.6 Simulations for Channel Characterization -- 2.6 UAV AG Propagation Models -- 2.6.1 AG Propagation Channel Model Types -- 2.6.2 Path‐Loss and Large‐Scale Fading Models -- 2.6.2.1 Free‐Space Path‐Loss Model -- 2.6.2.2 Floating‐Intercept Path‐Loss Model -- 2.6.2.3 Dual‐Slope Path‐Loss Model -- 2.6.2.4 Log‐Distance Path‐Loss Model -- 2.6.2.5 Modified FSPL Model -- 2.6.2.6 Two‐Ray PL Model -- 2.6.2.7 Log‐Distance FI Model -- 2.6.2.8 LOS/NLOS Mixture Path‐Loss Model -- 2.6.3 Airframe Shadowing -- 2.6.4 Small‐Scale Fading Models -- 2.6.5 Intermittent MPCs -- 2.6.6 Effect of Frequency Bands on Channel Models -- 2.6.7 MIMO AG Propagation Channel Models -- 2.6.8 Comparison of Different AG Channel Models -- 2.6.8.1 Large‐Scale Fading Models -- 2.6.8.2 Small‐Scale Fading Models -- 2.6.9 Comparison of Traditional Channel Models with UAV AG Propagation Channel Models -- 2.6.10 Ray Tracing Simulations -- 2.6.11 3GPP Channel Models for UAVs -- 2.7 Conclusions -- References -- Chapter 3 UAV Detection and Identification -- 3.1 Introduction -- 3.2 RF‐Based UAV Detection Techniques -- 3.2.1 RF Fingerprinting Technique -- 3.2.2 WiFi Fingerprinting Technique -- 3.3 Multistage UAV RF Signal Detection -- 3.3.1 Preprocessing Step: Multiresolution Analysis -- 3.3.2 The Naive Bayesian Decision Mechanism for RF Signal Detection -- 3.3.3 Detection of WiFi and Bluetooth Interference -- 3.4 UAV Classification Using RF Fingerprints -- 3.4.1 Feature Selection Using Neighborhood Components Analysis (NCA) -- 3.5 Experimental Results -- 3.5.1 Experimental Setup -- 3.5.2 Detection Results -- 3.5.3 UAV Classification Results -- 3.6 Conclusion -- Acknowledgments -- References -- Part II Cellular‐Connected UAV Communications -- Chapter 4 Performance Analysis for Cellular‐Connected UAVs 4.1 Introduction -- 4.1.1 Motivation -- 4.1.2 Related Works -- 4.1.3 Contributions and Chapter Structure -- 4.2 Modelling Preliminaries -- 4.2.1 Stochastic Geometry -- 4.2.2 Network Architecture -- 4.2.3 Channel Model -- 4.2.4 Blockage Modeling and LoS Probability -- 4.2.5 User Association Strategy and Link SINR -- 4.3 Performance Analysis -- 4.3.1 Exact Coverage Probability -- 4.3.2 Approximations for UAV Coverage Probability -- 4.3.2.1 Discarding NLoS and Noise Effects -- 4.3.2.2 Moment Matching -- 4.3.3 Achievable Throughput and Area Spectral Efficiency Analysis -- 4.4 System Design: Study Cases and Discussion -- 4.4.1 Analysis of Accuracy -- 4.4.2 Design Parameters -- 4.4.2.1 Impact of UAV Altitude -- 4.4.2.2 Impact of UAV Antenna Beamwidth -- 4.4.2.3 Impact of UAV Antenna Tilt -- 4.4.2.4 Impact of Different Types of Environment -- 4.4.3 Heterogeneous Networks - Tier Selection -- 4.4.4 Network Densification -- 4.5 Conclusion -- References -- Chapter 5 Performance Enhancements for LTE‐Connected UAVs: Experiments and Simulations -- 5.1 Introduction -- 5.2 LTE Live Network Measurements -- 5.2.1 Downlink Experiments -- 5.2.2 Path‐Loss Model Characterization -- 5.2.3 Uplink Experiments -- 5.3 Performance in LTE Networks -- 5.4 Reliability Enhancements -- 5.4.1 Interference Cancellation -- 5.4.2 Inter‐Cell Interference Control -- 5.4.3 CoMP -- 5.4.4 Antenna Beam Selection -- 5.4.5 Dual LTE Access -- 5.4.6 Dedicated Spectrum -- 5.4.7 Discussion -- 5.5 Summary and Outlook -- References -- Chapter 6 3GPP Standardization for Cellular‐Supported UAVs -- 6.1 Short Introduction to LTE and NR -- 6.1.1 LTE Physical Layer and MIMO -- 6.1.2 NR Physical Layer and MIMO -- 6.2 Drones Served by Mobile Networks -- 6.2.1 Interference Detection and Mitigation -- 6.2.2 Mobility for Drones -- 6.2.3 Need for Drone Identification and Authorization 6.3 3GPP Standardization Support for UAVs -- 6.3.1 Measurement Reporting Based on RSRP Level of Multiple Cells -- 6.3.2 Height, Speed, and Location Reporting -- 6.3.3 Uplink Power Control Enhancement -- 6.3.4 Flight Path Signalling -- 6.3.5 Drone Authorization and Identification -- 6.4 Flying Mode Detection in Cellular Networks -- References -- Chapter 7 Enhanced Cellular Support for UAVs with Massive MIMO -- 7.1 Introduction -- 7.2 System Model -- 7.2.1 Cellular Network Topology -- 7.2.2 System Model -- 7.2.3 Massive MIMO Channel Estimation -- 7.2.4 Massive MIMO Spatial Multiplexing -- 7.3 Single‐User Downlink Performance -- 7.3.1 UAV Downlink C& -- C Channel -- 7.4 Massive MIMO Downlink Performance -- 7.4.1 UAV Downlink C& -- C Channel -- 7.4.2 UAV-GUE Downlink Interplay -- 7.5 Enhanced Downlink Performance -- 7.5.1 UAV Downlink C& -- C Channel -- 7.5.2 UAV-GUE Downlink Interplay -- 7.6 Uplink Performance -- 7.6.1 UAV Uplink C& -- C Channel and Data Streaming -- 7.6.2 UAV-GUE Uplink Interplay -- 7.7 Conclusions -- References -- Chapter 8 High‐Capacity Millimeter Wave UAV Communications -- 8.1 Motivation -- 8.2 UAV Roles and Use Cases Enabled by Millimeter Wave Communication -- 8.2.1 UAV Roles in Cellular Networks -- 8.2.2 UAV Use Cases Enabled by High‐Capacity Cellular Networks -- 8.3 Aerial Channel Models at Millimeter Wave Frequencies -- 8.3.1 Propagation Considerations for Aerial Channels -- 8.3.1.1 Atmospheric Considerations -- 8.3.1.2 Blockages -- 8.3.2 Air‐to‐Air Millimeter Wave Channel Model -- 8.3.3 Air‐to‐Ground Millimeter Wave Channel Model -- 8.3.4 Ray Tracing as a Tool to Obtain Channel Measurements -- 8.4 Key Aspects of UAV MIMO Communication at mmWave Frequencies -- 8.5 Establishing Aerial mmWave MIMO Links -- 8.5.1 Beam Training and Tracking for UAV Millimeter Wave Communication 8.5.2 Channel Estimation and Tracking in Aerial Environments -- 8.5.3 Design of Hybrid Precoders and Combiners -- 8.6 Research Opportunities -- 8.6.1 Sensing at the Tower -- 8.6.2 Joint Communication and Radar -- 8.6.3 Positioning and Mapping -- 8.7 Conclusions -- References -- Part III UAV‐Assisted Wireless Communications -- Chapter 9 Stochastic Geometry‐Based Performance Analysis of Drone Cellular Networks -- 9.1 Introduction -- 9.2 Overview of the System Model -- 9.2.1 Spatial Model -- 9.2.2 3GPP‐Inspired Mobility Model -- 9.2.3 Channel Model -- 9.2.4 Metrics of Interest -- 9.3 Average Rate -- 9.4 Handover Probability -- 9.5 Results and Discussion -- 9.5.1 Density of Interfering DBSs -- 9.5.2 Average Rate -- 9.5.3 Handover Probability -- 9.6 Conclusion -- Acknowledgment -- References -- Chapter 10 UAV Placement and Aerial-Ground Interference Coordination -- 10.1 Introduction -- 10.2 Literature Review -- 10.3 UABS Use Case for AG‐HetNets -- 10.4 UABS Placement in AG‐HetNet -- 10.5 AG‐HetNet Design Guidelines -- 10.5.1 Path‐Loss Model -- 10.5.1.1 Log‐Distance Path‐Loss Model -- 10.5.1.2 Okumura-Hata Path‐Loss Model -- 10.6 Inter‐Cell Interference Coordination -- 10.6.1 UE Association and Scheduling -- 10.7 Simulation Results -- 10.7.1 5pSE with UABSs Deployed on Hexagonal Grid -- 10.7.1.1 5pSE with Log‐Normal Path‐Loss Model -- 10.7.1.2 5pSE with Okumura-Hata Path‐Loss Model -- 10.7.2 5pSE with GA‐Based UABS Deployment Optimization -- 10.7.2.1 5pSE with Log‐Normal Path‐Loss Model -- 10.7.2.2 5pSE with Okumura-Hata Path‐Loss model -- 10.7.3 Performance Comparison Between Fixed (Hexagonal) and Optimized UABS Deployment with eICIC and FeICIC -- 10.7.3.1 Influence of LDPLM on 5pSE -- 10.7.3.2 Influence of OHPLM on 5pSE -- 10.7.4 Comparison of Computation Time for Different UABS Deployment Algorithms -- 10.8 Concluding remarks -- References Chapter 11 Joint Trajectory and Resource Optimization |
| title | UAV communications for 5G and beyond |
| title_auth | UAV communications for 5G and beyond |
| title_exact_search | UAV communications for 5G and beyond |
| title_exact_search_txtP | UAV communications for 5G and beyond |
| title_full | UAV communications for 5G and beyond edited by Yong Zeng, Ismail Guvenc, Rui Zhang, Giovanni Geraci, David W. Matolak |
| title_fullStr | UAV communications for 5G and beyond edited by Yong Zeng, Ismail Guvenc, Rui Zhang, Giovanni Geraci, David W. Matolak |
| title_full_unstemmed | UAV communications for 5G and beyond edited by Yong Zeng, Ismail Guvenc, Rui Zhang, Giovanni Geraci, David W. Matolak |
| title_short | UAV communications for 5G and beyond |
| title_sort | uav communications for 5g and beyond |
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