Resource Optimization in Heterogeneous Networks With Multi Connectivity

다국어 초록 (Multilingual Abstract)

Future wireless networks, driven by increasing demand for high data rates and massive connectivity, are expected to face more severe capacity constraints. To address the capacity challenges, heterogeneous networks (HetNets) integrate macro cells and small cells to enhance network capacity and coverage. To maintain high data rates while ensuring mobility robustness, dual connectivity within HetNets enables the primary macro cell to manage the control plane while distributing user equipment (UE) data traffic between the macro and secondary small cells. DC with traffic splitting distributes UE data traffic between macro and small cells based on dynamic cell load and channel conditions. Without traffic splitting, the network must rely on high transmission power to meet rate demands, and uneven load distribution can degrade quality of service (QoS). Therefore, an intelligent traffic-splitting strategy is essential in dual connectivity to minimize total transmission power and maintain balanced load across the network, ensuring efficient and reliable service delivery. Moreover, with dynamic user distribution and varying channel conditions, selecting the optimal access scheme under dual connectivity becomes critical for enhancing network performance.
Part I of the thesis provides an introduction to dual connectivity (DC), explains its various types, and discusses the use of spectrum within the DC framework. Chapter 1 introduces the concept of DC and explains its classification based on deployment scenarios and radio access technologies. Chapter 2 focuses on inter-radio access technology (inter-RAT) DC, which enables connectivity between different types of networks. The architectural options for splitting user traffic across inter-RAT DCs are presented, along with a discussion of their respective advantages. Chapter 3 describes spectrum utilization in DC-based systems, emphasizing multiple access techniques and mechanisms that enhance spectrum efficiency and enable flexible resource sharing across connected cells.
Part II of the thesis focuses on traffic splitting under DC-enabled heterogeneous networks (HetNets). In Chapter 4, we propose an adaptive traffic-splitting mechanism for DC UEs in heterogeneous networks (HetNets). Due to asymmetric channel conditions between macro and small cells, an uneven traffic split often results in high transmission power to meet UE rate requirements. To address this inefficiency, an optimal split-ratio expression is derived that minimizes total transmission power while satisfying user data rate demands. A heuristic algorithm is designed that iteratively computes the optimal traffic split for each DC UE, efficiently distributing the UE data traffic across macro and small cells. Using NS-3, we verify the analysis and show that the proposed algorithm minimizes total transmission power while satisfying QoS requirements. In addition, we show the impact of user mobility and the number of small cells on the data rate splitting ratio. In Chapter 5, a joint traffic-splitting and handover scheme is proposed to balance cell load and meet QoS demands. Due to user mobility and variable channel conditions, uneven traffic distribution across the network can lead to load imbalances that degrade QoS. An optimal split ratio is derived by considering both channel quality and current cell load. Based on the derived split ratio, the proposed algorithm distributes user data traffic between macro and small cells to balance network load. If certain cells remain overloaded even after splitting DC UEs, the algorithm initiates handovers for edge users from macro cells to lower congestion and further reduces load variance across the network. Simulation results show that the proposed algorithm achieves a more even load distribution than other load balancing algorithms and increases network throughput and the number of QoS-satisfied users. In Chapter 6, we propose a power minimization algorithm for DC-based HetNets employing hybrid Non-Orthogonal Multiple Access (NOMA). The conventional Orthogonal Frequency Division Multiple Access (OFDMA) scheme under DC suffers from bandwidth limitations. The proposed algorithm utilizes hybrid NOMA with DC to enable energy-efficient and spectrum-efficient next-generation multiple access for future wireless networks while satisfying QoS requirements and self-interference cancellation constraints. A theoretical expression is derived to determine the minimum channel gain gap required to group users under NOMA with higher energy efficiency than OFDMA. The simulation results demonstrate that the proposed scheme achieves a power minimization of 31.25% and 7.56% compared to NOMA with single connectivity and OFDMA with dual connectivity, respectively.

목차 (Table of Contents)

• Vita i
• Acknowledgments ii
• Abstract iii
• Table of Contents vi
• List of Figures ix
• List of Tables xi
• Nomenclature xii
• I Wireless Networks Preliminaries 1
• 1 Introduction 2
• 1.1 Heterogenous Networks 3
• 1.2 Dual Connectivity within Heterogeneous Networks 4
• 2 Overview of Inter-RAT Dual Connectivity 7
• 2.1 What is Inter-RAT Dual Connectivity 7
• 2.2 Advantages of 3C Configuration Over 1A 9
• 2.2.1 Throughput Enhancement 9
• 2.2.2 Resource Utilization and Efficiency 9
• 3 Spectrum Utilization under Dual Connectivity 12
• 3.1 Overview 12
• 3.2 Orthogonal Frequency Division Multiple Access 13
• 3.3 Non-Orthogonal Multiple Access 15
• 3.4 Hybrid Multiple Access 18
• II Traffic Splitting Under Dual Connectivity Based HetNets 20
• 4 Adaptive Traffic Splitting for Transmission Power Minimization with QoS Enhancement in 5G HetNets 21
• 4.1 Introduction 21
• 4.2 System Model and Problem Formulation 25
• 4.2.1 Network Architecture 25
• 4.2.2 SINR Estimation 26
• 4.2.3 Problem Formulation 28
• 4.3 An Analytical Solution 30
• 4.4 The Proposed Algorithm 33
• 4.5 Complexity and Convergence Time Analysis 39
• 4.6 Performance Evaluation 41
• 4.6.1 Simulation Environment 41
• 4.6.2 Impact of the User Trajectory 44
• 4.6.3 Impact of a User Trajectory with Multiple Small Cells 46
• 4.6.4 Random Deployment of Small Cells and the RWP Mobility Model 47
• 4.6.5 Impact of Network Loads 49
• 4.7 Conclusion 50
• 5 Load Balancing with Traffic Splitting for QoS Enhancement in 5G HetNets 52
• 5.1 Research Necessity 52
• 5.2 System Model and Problem Formulation 55
• 5.2.1 Network Architecture 55
• 5.2.2 Measurement of Cell Load 57
• 5.2.3 Problem Formulation 58
• 5.3 An Analytical Solution 60
• 5.4 The Proposed Algorithm 63
• 5.5 Complexity and Convergence Time Analysis 69
• 5.6 Performance Evaluation 72
• 5.6.1 Simulation Environment 72
• 5.6.2 Impact of the Proposed Algorithm on Load Distribution 73
• 5.6.3 Impact on Network Throughput and QoS 76
• 5.6.4 Impact on Handover Counts 77
• 5.6.5 Impact of Small cell Density on the Proposed Algorithm 79
• 5.6.6 Impact of Load Variations 81
• 5.7 Conclusion 82
• 6 Energy-Efficient Hybrid NOMA With Dual Connectivity in HetNets 85
• 6.1 Research Necessity 85
• 6.2 System Model 88
• 6.2.1 System Description and Assumptions 88
• 6.2.2 Spectrum Utilization in OFDMA and NOMA 90
• 6.2.3 SINR Estimation 90
• 6.2.4 Problem Formulation 92
• 6.3 An Analytical Solution 95
• 6.4 The Proposed Algorithm 97
• 6.5 Performance Evaluation 102
• 6.5.1 The Simulation Environment 102
• 6.5.2 Feasibility of NOMA Grouping with Dual Connectivity 104
• 6.5.3 Impact of Varying Data Rate Requirements on NOMA Grouping 107
• 6.5.4 Impact of NOMA Groups Configurations on Transmission Power 108
• 6.5.5 Impacts of Network Load 109
• 6.5.6 Impacts of Traffic Load 111
• 6.6 Closing Remarks 112
• Publications 113
• References 114