5G and Beyond Wireless Communication Networks

• Autore: Sun Haijian
• Pubblicazione: Newark : , : John Wiley & Sons, Incorporated, , 2023; ©2023
• Edizione: 1st ed.
• Descrizione fisica: 1 online resource (211 pages)
• Disciplina: 621.38456
• Soggetto topico: 5G mobile communication systems; Wireless communication systems
• Altri autori: HuRose Qingyang QianYi
• Nota di contenuto: Cover -- Title Page -- Copyright -- Contents -- About the Authors -- Preface -- Acknowledgments -- Chapter 1 Introduction to 5G and Beyond Network -- 1.1 5G and Beyond System Requirements -- 1.1.1 Technical Challenges -- 1.2 Enabling Technologies -- 1.2.1 5G New Radio -- 1.2.1.1 Non‐orthogonal Multiple Access (NOMA) -- 1.2.1.2 Channel Codes -- 1.2.1.3 Massive MIMO -- 1.2.1.4 Other 5G NR Techniques -- 1.2.2 Mobile Edge Computing (MEC) -- 1.2.3 Hybrid and Heterogeneous Communication Architecture for Pervasive IoTs -- 1.3 Book Outline -- Chapter 2 5G Wireless Networks with Underlaid D2D Communications -- 2.1 Background -- 2.1.1 MU‐MIMO -- 2.1.2 D2D Communication -- 2.1.3 MU‐MIMO and D2D in 5G -- 2.2 NOMA‐Aided Network with Underlaid D2D -- 2.3 NOMA with SIC and Problem Formation -- 2.3.1 NOMA with SIC -- 2.3.2 Problem Formation -- 2.4 Precoding and User Grouping Algorithm -- 2.4.1 Zero‐Forcing Beamforming -- 2.4.1.1 First ZF Precoding -- 2.4.1.2 Second ZF Precoding -- 2.4.2 User Grouping and Optimal Power Allocation -- 2.4.2.1 First ZF Precoding -- 2.4.2.2 Second ZF Precoding -- 2.5 Numerical Results -- 2.6 Summary -- Chapter 3 5G NOMA‐Enabled Wireless Networks -- 3.1 Background -- 3.2 Error Propagation in NOMA -- 3.3 SIC and Problem Formulation -- 3.3.1 SIC with Error Propagation -- 3.3.2 Problem Formation -- 3.4 Precoding and Power Allocation -- 3.4.1 Precoding Design -- 3.4.2 Case Studies for Power Allocation -- 3.4.2.1 Case I -- 3.4.2.2 Case II -- 3.5 Numerical Results -- 3.6 Summary -- Chapter 4 NOMA in Relay and IoT for 5G Wireless Networks -- 4.1 Outage Probability Study in a NOMA Relay System -- 4.1.1 Background -- 4.1.2 System Model -- 4.1.2.1 NOMA Cooperative Scheme -- 4.1.2.2 NOMA TDMA Scheme -- 4.1.3 Outage Probability Analysis -- 4.1.3.1 Outage Probability in NOMA Cooperative Scheme -- 4.1.4 Outage Probability in NOMA TDMA Scheme. ; 4.1.5 Outage Probability with Error Propagation in SIC -- 4.1.5.1 Outage Probability in NOMA Cooperative Scheme with EP -- 4.1.5.2 Outage Probability in NOMA TDMA Scheme with EP -- 4.1.6 Numerical Results -- 4.2 NOMA in a mmWave‐Based IoT Wireless System with SWIPT -- 4.2.1 Introduction -- 4.2.2 System Model -- 4.2.2.1 Phase 1 Transmission -- 4.2.2.2 Phase 2 Transmission -- 4.2.3 Outage Analysis -- 4.2.3.1 UE 1 Outage Probability -- 4.2.3.2 UE 2 Outage Probability -- 4.2.3.3 Outage at High SNR -- 4.2.3.4 Diversity Analysis for UE 2 -- 4.2.4 Numerical Results -- 4.2.5 Summary -- Chapter 5 Robust Beamforming in NOMA Cognitive Radio Networks: Bounded CSI -- 5.1 Background -- 5.1.1 Related Work and Motivation -- 5.1.1.1 Linear EH Model -- 5.1.1.2 Non‐linear EH Model -- 5.1.2 Contributions -- 5.2 System and Energy Harvesting Models -- 5.2.1 System Model -- 5.2.2 Non‐linear EH Model -- 5.2.3 Bounded CSI Error Model -- 5.2.3.1 NOMA Transmission -- 5.3 Power Minimization‐Based Problem Formulation -- 5.3.1 Problem Formulation -- 5.3.2 Matrix Decomposition -- 5.4 Maximum Harvested Energy Problem Formulation -- 5.4.1 Complexity Analysis -- 5.5 Numerical Results -- 5.5.1 Power Minimization Problem -- 5.5.2 Energy Harvesting Maximization Problem -- 5.6 Summary -- Chapter 6 Robust Beamforming in NOMA Cognitive Radio Networks: Gaussian CSI -- 6.1 Gaussian CSI Error Model -- 6.2 Power Minimization‐Based Problem Formulation -- 6.2.1 Bernstein‐Type Inequality I -- 6.2.2 Bernstein‐Type Inequality II -- 6.3 Maximum Harvested Energy Problem Formulation -- 6.3.1 Complexity Analysis -- 6.4 Numerical Results -- 6.4.1 Power Minimization Problem -- 6.4.2 Energy Harvesting Maximization Problem -- 6.5 Summary -- Chapter 7 Mobile Edge Computing in 5G Wireless Networks -- 7.1 Background -- 7.2 System Model -- 7.2.1 Data Offloading -- 7.2.2 Local Computing. ; 7.3 Problem Formulation -- 7.3.1 Update pk, tk, and fk -- 7.3.2 Update Lagrange Multipliers -- 7.3.3 Update Auxiliary Variables -- 7.3.4 Complexity Analysis -- 7.4 Numerical Results -- 7.5 Summary -- Chapter 8 Toward Green MEC Offloading with Security Enhancement -- 8.1 Background -- 8.2 System Model -- 8.2.1 Secure Offloading -- 8.2.2 Local Computing -- 8.2.3 Receiving Computed Results -- 8.2.4 Computation Efficiency in MEC Systems -- 8.3 Computation Efficiency Maximization with Active Eavesdropper -- 8.3.1 SCA‐Based Optimization Algorithm -- 8.3.2 Objective Function -- 8.3.3 Proposed Solution to P4 with given (λk,βk) -- 8.3.4 Update (λk,βk) -- 8.4 Numerical Results -- 8.5 Summary -- Chapter 9 Wireless Systems for Distributed Machine Learning -- 9.1 Background -- 9.2 System Model -- 9.2.1 FL Model Update -- 9.2.2 Gradient Quantization -- 9.2.3 Gradient Sparsification -- 9.3 FL Model Update with Adaptive NOMA Transmission -- 9.3.1 Uplink NOMA Transmission -- 9.3.2 NOMA Scheduling -- 9.3.3 Adaptive Transmission -- 9.4 Scheduling and Power Optimization -- 9.4.1 Problem Formulation -- 9.5 Scheduling Algorithm and Power Allocation -- 9.5.1 Scheduling Graph Construction -- 9.5.2 Optimal scheduling Pattern -- 9.5.3 Power Allocation -- 9.6 Numerical Results -- 9.7 Summary -- Chapter 10 Secure Spectrum Sharing with Machine Learning: An Overview -- 10.1 Background -- 10.1.1 SS: A Brief History -- 10.1.2 Security Issues in SS -- 10.2 ML‐Based Methodologies for SS -- 10.2.1 ML‐Based CRN -- 10.2.1.1 Spectrum Sensing -- 10.2.1.2 Spectrum Selection -- 10.2.1.3 Spectrum Access -- 10.2.1.4 Spectrum Handoff -- 10.2.2 Database‐Assisted SS -- 10.2.2.1 ML‐Based EZ Optimization -- 10.2.2.2 Incumbent Detection -- 10.2.2.3 Channel Selection and Transaction -- 10.2.3 ML‐Based LTE‐U/LTE‐LAA -- 10.2.3.1 ML‐Based LBT Methods -- 10.2.3.2 ML‐Based Duty Cycle Methods. ; 10.2.3.3 Game‐Theory‐Based Methods -- 10.2.3.4 Distributed‐Algorithm‐Based Methods -- 10.2.4 Ambient Backscatter Networks -- 10.2.4.1 Information Extraction -- 10.2.4.2 Operating Mode Selection and User Coordination -- 10.2.4.3 AmBC‐CR Methods -- 10.3 Summary -- Chapter 11 Secure Spectrum Sharing with Machine Learning: Methodologies -- 11.1 Security Concerns in SS -- 11.1.1 Primary User Emulation Attack -- 11.1.2 Spectrum Sensing Data Falsification Attack -- 11.1.3 Jamming Attacks -- 11.1.4 Intercept/Eavesdrop -- 11.1.5 Privacy Issues in Database‐Assisted SS Systems -- 11.2 ML‐Assisted Secure SS -- 11.2.1 State‐of‐the‐Art Methods of Defense Against PUE Attack -- 11.2.1.1 ML‐Based Detection Methods -- 11.2.1.2 Robust Detection Methods -- 11.2.1.3 ML‐Based Attack Methods -- 11.2.2 State‐of‐the‐Art Methods of Defense Against SSDF Attack -- 11.2.2.1 Outlier Detection Methods -- 11.2.2.2 Reputation‐Based Detection Methods -- 11.2.2.3 SSDF and PUE Combination Attacks -- 11.2.3 State‐of‐the‐Art Methods of Defense Against Jamming Attacks -- 11.2.3.1 ML‐Based Anti‐Jamming Methods -- 11.2.3.2 Attacker Enhanced Anti‐Jamming Methods -- 11.2.3.3 AmBC Empowered Anti‐Jamming Methods -- 11.2.4 State‐of‐the‐Art Methods of Defense Against Intercept/Eavesdrop -- 11.2.4.1 RL‐Based Anti‐Eavesdropping Methods -- 11.2.5 State‐of‐the‐Art ML‐Based Privacy Protection Methods -- 11.2.5.1 Privacy Protection for PUs in SS Networks -- 11.2.5.2 Privacy Protection for SUs in SS Networks -- 11.2.5.3 Privacy Protection for ML Algorithms -- 11.3 Summary -- Chapter 12 Open Issues and Future Directions for 5G and Beyond Wireless Networks -- 12.1 Joint Communication and Sensing -- 12.2 Space‐Air‐Ground Communication -- 12.3 Semantic Communication -- 12.4 Data‐Driven Communication System Design -- Appendix A Proof of Theorem 5.1 -- Bibliography -- Index -- EULA.
• Sommario/riassunto: This book delves into the advancements and challenges of 5G and beyond wireless communication networks. It covers a range of topics including new radio technologies, massive MIMO, and non-orthogonal multiple access. The book also explores device-to-device communications, mobile edge computing, and secure spectrum sharing with machine learning. It is aimed at researchers, practitioners, and students in the field of electrical and computer engineering, providing insights into the future directions and potential applications of wireless networks. The authors, Haijian Sun, Rose Qingyang Hu, and Yi Qian, bring expertise from academia to discuss the technical requirements and enabling technologies for next-generation networks.
• Titolo autorizzato: 5G and Beyond Wireless Communication Networks
• ISBN: 9781119089490; 1119089492; 9781119089469; 1119089468
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9911019090903321
• Lo trovi qui: Univ. Federico II
• Serie: IEEE Press Series