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.