6G Multimedia Communications Analysis, Design, and Optimisation
Produktdetaljer
Biografisk notat
Nguyen-Son Vo, PhD, works with the Institute of Fundamental Applied Sciences at Duy Tan University in Vietnam. His research interests focus on content caching and delivering in wireless networks, multimedia wireless communications, quality of experience and sustainability provision in wireless networks for smart cities, and for disaster and environment management.
Trung Q. Duong (Fellow of IEEE and Fellow of AAIA) is a Canada Excellence Research Chair (CERC) and a Full Professor at Memorial University of Newfoundland, Canada. He is a Research Chair of the Royal Academy of Engineering and also an adjunct Chair Professor in Telecommunications at Queen's University Belfast, UK. His research interests include quantum communications, quantum machine learning, quantum optimization, and wireless communications.
Trang Hoang, PhD, is an Associate Professor at the Faculty of Electricals-Electronics Engineering, Ho Chi Minh City University of Technology, VNU-HCM, Vietnam. His research interests include quantum-inspired machine learning, optimization, AI for IC design and wireless communications.
An up-to-date examination of the latest technologies and research impacting 6G multimedia communications
In 6G Multimedia Communications: Analysis, Design, and Optimization, a team of distinguished researchers delivers a comprehensive new discussion of the theory, models, techniques, analysis, design, and optimization of multimedia communications in 6G networks. The authors explain the potential of multimedia communication systems using recent edge techniques, including caching, resource sharing, power allocation, multicasting, and D2D communications.
You'll find solutions to various real-world application- and service-level problems in industries like surveillance, entertainment, eHealth, eLearning, smart home and environment management, and public safety.
- A thorough introduction to cross-layer optimization design for multimedia applications and services in content delivery networks
- Comprehensive explorations of social-aware resource sharing and caching for video transmission in ultra-dense networks
- Practical discussions of MEC technology, mobile applications, and smart city scenarios
- Complete treatment of future wireless content delivery network technology for multimedia communications
Perfect for working telecommunication professionals, 6G Multimedia Communications will also benefit researchers and graduate students with an interest in cutting-edge network technology.
Contents
Preface
Acronyms
1 AN OVERVIEW OF MULTIMEDIA COMMUNICATIONS
1.1 Advanced Applications and Services in 6G Networks
1.2 Multimedia Applications and Services in 6G Networks
1.3 Techniques for 6G Multimedia Communications
1.3.1 Edge computing assisted multimedia communications
1.3.2 Multicasting assisted multimedia communications
1.3.3 D2D multimedia communications
1.3.4 Caching assisted multimedia communications
1.4 Multimedia Communications in 6G Networks: Challenges and Research Directions
1.4.1 Challenges
1.4.2 Research directions
1.5 Conclusion
2 ENCODING RATE SELECTION AND PROBABILISTIC
CACHING FOR VIDEO OFFLOADING IN DENSE D2D NETWORKS
2.1 Introduction
2.2 RSC System for Video Offloading
2.2.1 RSC components
2.2.2 Preliminary RSC models
2.2.2.1 Video popularity model
2.2.2.2 Rate-distortion model
2.2.2.3 Homogeneous Poisson Point Process model
2.2.3 RSC operation description
2.3 Analysis and Formulation of RSC Model for Video Offloading
2.3.1 Hit probabilities
2.3.2 Achievable rate probability
2.3.3 Average playback quality and resource consumption 36
2.4 RSC Optimisation Design
2.4.1 RSC optimisation problem
2.4.2 RSC optimisation solution with genetic algorithms
2.5 Performance Evaluation of RSC
2.5.1 System setting
2.5.2 GA convergence evaluation
2.5.3 RSC evaluation
2.6 Conclusion
3 SPECTRUM SHARING AND POWER ALLOCATION FOR VIDEO TRANSMISSION IN MULTIHOP MULTI-PATH D2D NETWORKS
3.1 Introduction
3.2 SPA Model for Video Transmission in MHMP D2D Networks
3.3 Analysis and Formulations of SPA Model
3.3.1 MHMP D2D capacity
3.3.2 Normal cellular capacity
3.3.3 Average delivery capacity at RU
3.3.4 SINR at SH
3.4 SPA Optimisation Design
3.4.1 SPA optimisation problem
3.4.2 SPA optimisation with GA
3.5 Performance Evaluation of SPA
3.5.1 Parameter setting
3.5.2 GA convergence evaluation
3.5.3 SPA evaluation
3.5.3.1 Capacity performance
3.5.3.2 Power consumption performance
3.6 Conclusion
4 SOCIAL-AWARE SPECTRUM SHARING AND CACHING HELPER SELECTION FOR VIDEO MULTICASTING IN D2D NETWORKS
4.1 Introduction
4.2 System Model for Video Multicasting in D2D Networks with SSC
4.3 Analysis and Formulations of SSC .
4.3.1 Social relationship
4.3.2 Wireless channels
4.3.3 Capacity at RUs .
4.3.4 Capacity fluctuation amongst RUs
4.3.5 SINR at SHs
4.4 SSC Optimisation Design
4.4.1 SSC optimisation problem
4.4.2 SSC optimisation solution with GA
4.5 Performance Evaluation of SSC
4.5.1 System setting
4.5.2 GA convergence evaluation
4.5.3 SSC evaluation
4.6 Conclusion
5 RESOURCE SHARING ANDMULTI-TIER MULTI-RATE CACHING FOR COOPERATIVE VIDEO STREAMING IN ULTRA-DENSE NETWORKS
5.1 Introduction
5.2 RMC Model for Cooperative Video Streaming
5.3 Analysis and Formulation of RMC Model
5.3.1 Preliminary analysis and formulation
5.3.1.1 Achievable rate probability at SHs
5.3.1.2 Achievable rate probability at VHs
5.3.1.3 Achievable rate probability at RUs
5.3.2 Objective function
5.3.3 Resource consumption
5.4 RMC Optimisation Design
5.5 Performance Evaluation of RMC
5.6 Conclusion
6 SOCIAL-AWARE RESOURCE SHARING AND CACHING FOR COOPERATIVE VIDEO TRANSMISSION IN ULTRADENSE NETWORKS
6.1 Introduction
6.2 SRC Model for Cooperative Video Transmission
6.3 Formulation of SRC Model
6.3.1 Social relationship of D2D pairs
6.3.2 Wireless channels
6.3.3 System delivery capacity
6.3.3.1 Capacity delivered to SHs
6.3.3.2 Capacity delivered to VHs
6.3.3.3 Capacity delivered to RUs
6.3.4 Objective functions
6.4 SRC Optimisation Design
6.5 Performance Evaluation of SRC
6.5.1 System setting
6.5.2 System performance versus C
6.5.3 System performance versus δ
6.5.4 System performance versus α
6.5.5 System performance versus N
6.5.6 System performance versus J
6.5.7 System performance versus γ0
6.5.8 System performance versus distance between MBS
and MUs
6.6 Conclusion
7 SPECTRUM SHARING AND CACHING FOR MULTIMEDIA APPLICATIONS AND SERVICES IN CONTENT DELIVERY NETWORKS
7.1 Introduction
7.2 System Model of SCF
7.3 Analysis and Formulation of SCF
7.3.1 Hit ratio
7.3.2 System delivery capacity
7.4 SCF Optimisation Design
7.4.1 NRO
7.4.2 SCO
7.5 Performance Evaluation of SCF
7.5.1 System setting
7.5.2 Performance metrics
7.5.2.1 Hit ratio performance
7.5.2.2 System delivery capacity performance
7.6 Conclusion
8 JOINT ENERGY, BANDWIDTH AND QUALITY OPTIMISATION FOR MULTIMEDIA APPLICATIONS AND SERVICES IN CONTENT DELIVERY NETWORKS
8.1 Introduction
8.2 M-IoT system with EBQ Framework
8.3 Analysis and Formulation of EBQ Optimisation Framework
8.3.1 Source video packetisation scheme
8.3.2 Energy consumption
8.3.3 Bandwidth consumption
8.3.4 Quality guarantee
8.4 ARA Optimisation Problem and Solution
8.4.1 ARA optimisation problem
8.4.2 Solution with GA
8.5 Performance Evaluation
8.5.1 Parameters setting
8.5.2 Convergence rate of GA
8.5.3 Performance metrics
8.5.3.1 EBQ performance versus skewed importance
parameter αi
8.5.3.2 EBQ performance versus quality guarantee
coefficient δD
8.5.3.3 EBQ performance versus bandwidth consumption
coefficient δB
8.6 Conclusion
9 ACTIVE DUTY SCHEDULING AND ENCODING RATE ALLOCATION FOR MULTIMEDIA APPLICATIONS AND SERVICES IN CONTENT DELIVERY NETWORKS
9.1 Introduction
9.2 ADS-ARA Model
9.3 ADS-ARA Formulation and Analysis
9.3.1 Capture energy consumption
9.3.2 Packetisation and transmission energy consumption
9.3.2.1 Source video analysis
9.3.2.2 Packetisation energy consumption
9.3.2.3 Transmission energy consumption
9.3.3 Playback quality
9.3.4 Backhaul bandwidth consumption
9.4 ADS-ARA Optimisation Design
9.4.1 ADS problem and solution
9.4.2 ARA problem and solution
9.5 Performance Evaluation of ADS-ARA
9.5.1 System setting
9.5.2 ADS performance evaluation
9.5.3 ARA performance evaluation
9.5.3.1 ARA performance versus α
9.5.3.2 ARA performance versus δD
9.6 Conclusion
10 OPTIMAL COOPERATIVE VIDEO STREAMING IN DENSE D2D NETWORKS
10.1 Introduction
10.2 CVS System with RDO in Dense D2D Networks
10.3 RDO Formulation and Analysis
10.3.1 RDM and LMDC-FEC packetisation
10.3.2 End-to-end reconstructed distortion
10.3.3 Energy consumption .
10.3.4 SINR at SHs
10.4 RDO Optimisation Design
10.4.1 RDO problem
10.4.2 GA solution
10.5 Performance Evaluation of RDO
10.5.1 System setting
10.5.2 Convergence evaluation of GA
10.5.3 Performance metrics
10.5.3.1 Performance metrics versus α
10.5.3.2 Performance metrics versus εh
10.5.3.3 Performance metrics versus E
10.5.3.4 Performance metrics versus γ(0) and H
10.5.3.5 Performance metrics versus ε(0)
10.6 Conclusion
11 CROSS-LAYER OPTIMISATION DESIGN FOR MULTIMEDIA APPLICATIONS AND SERVICES IN CONTENT DELIVERY NETWORKS
11.1 Introduction
11.2 CLD Framework for MAS
11.2.1 APP layer
11.2.2 DLK layer
11.2.3 PHY layer
11.3 Analysis and Formulation of CLD Optimisation Framework
11.3.1 Real-time traffic
11.3.2 Non-real-time traffic
11.3.3 System performance metrics
11.3.3.1 PDR
11.3.3.2 PER
11.3.3.3 Throughput and delay
11.4 CLD Problem and Solution
11.4.1 Optimisation problem for MAS
11.4.1.1 Minimum PDR
11.4.1.2 Minimum PER
11.4.2 Optimisation problem for video streaming
11.5 Performance Evaluation of CLD
11.5.1 CLD for MAS
11.5.1.1 Dependence on arrival rate
11.5.1.2 Dependence on average SNR
11.5.2 CLD for video streaming
11.6 Conclusion
Index
Produktdetaljer
Biografisk notat
Nguyen-Son Vo, PhD, works with the Institute of Fundamental Applied Sciences at Duy Tan University in Vietnam. His research interests focus on content caching and delivering in wireless networks, multimedia wireless communications, quality of experience and sustainability provision in wireless networks for smart cities, and for disaster and environment management.
Trung Q. Duong (Fellow of IEEE and Fellow of AAIA) is a Canada Excellence Research Chair (CERC) and a Full Professor at Memorial University of Newfoundland, Canada. He is a Research Chair of the Royal Academy of Engineering and also an adjunct Chair Professor in Telecommunications at Queen's University Belfast, UK. His research interests include quantum communications, quantum machine learning, quantum optimization, and wireless communications.
Trang Hoang, PhD, is an Associate Professor at the Faculty of Electricals-Electronics Engineering, Ho Chi Minh City University of Technology, VNU-HCM, Vietnam. His research interests include quantum-inspired machine learning, optimization, AI for IC design and wireless communications.