m Formation 14 2.3.1 NOMA with SIC 2.3.2 Problem Formation 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 Numerical Results Summary 19 Contents 5G NOMA-Enabled Wireless Networks Background 21 Error Propagation in NOMA SIC and Problem Formulation 3.3.1 SIC with Error Propagation 3.3.2 Problem Formation Precoding and Power Allocation 3.4.1 Precoding Design 25 3.4.2 Case Studies for Power Allocation 3.4.2.1 Case I 3.4.2.2 Case II Numerical Results Summary NOMA in Relay and loT for 5G Wireless Networks Outage Probability Study in a NOMA Relay System 4.1.1 Background 31 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 NOMA in a mmWave-Based IoT Wireless System with SWIPT 4.2.1 Introduction 41 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 48 Robust Beamforming in NOMA Cognitive Radio Networks: Bounded CSI 51 Background 51 5.1.1 Related Work and Motivation 5.1.1.1 Linear EH Model Contents 5.1.1.2 Non-linear EH Model 5.1.2 Contributions 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 Power Minimization-Based Problem Formulation 5.3.1 Problem Formulation 5.3.2 Matrix Decomposition Maximum Harvested Energy Problem Formulation 5.4.1 Complexity Analysis Numerical Results 5.5.1 Power Minimization P