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Table of contents
1. Introduction
1.1 Introduction
1.2 Background and motivation
1.3 Problem Statement
1.4 Sub-problems
1.4.1 Sub-problem 1: Channel coding with high energy cost
1.4.2 Sub-Problem 2: Network scalability
1.4.3 Sub-problem 3: Low modulation data rates
1.5 Hypotheses
1.5.1 A channel-aware adaptive channel coding approach
1.5.2 An adaptive transmission repetition number selection
1.5.3 Spread spectrum and clustering approach
1.6 Importance and benets of the study
1.7 Delimitation and assumptions of the study
1.8 Research Methodology
1.9 Contributions and Outputs of the Study
1.10 Thesis Outline
2. The Narrowband Internet of Things State of Art, Challenges, and Opportunities
2.1 Introduction
2.1.1 Background and motivation
2.2 An overview on the LPWANs and the NB-IoT
2.2.1 Comparison of the NB-IoT and other IoT Technologies
2.2.2 NB-IoT and LoRa PHY layer comparison
2.3 NB-IoT design objectives
2.4 Most Common NB-IoT Applications and Associated Network Re-sources Challenges
2.4.1 Smart metering
2.4.2 Smart Cities
2.4.3 Indoor and Outdoor Localisation Applications
2.4.4 Farming and forestry: Monitoring livestock
2.4.5 Industry: NB-IoT on pallets and pipelines
2.5 The NB-IoT as part of 5G cellular IoT
2.6 SDN and NFV for NB-IoT within 5G Systems
2.7 Energy ecient NB-IoT Channel Coding (CC) schemes
2.7.1 Why Is Energy Ecient Channel Coding Important for NB-IoT 52
2.7.2 Existing NB-IoT Energy-Ecient Channel Coding (CC) ap-proaches
2.8 Data rate enhanced NB-IoT modulation selection schemes
2.9 Link Adaptation Schemes for enhanced NB-IoT scalability
2.10 An overview on the NB-IoT spectrum sharing and clustering
2.10.1 Spectrum Sharing Techniques in licensed band IoT systems
2.10.2 Spread Spectrum challenges in NB-IoT systems
2.10.3 Clustering Approaches for energy-ecient NB-IoT
2.10.4 Energy-Ecient Network coding techniques for NB-IoT systems
2.11 The NB-IoT performance Challenges and open issues
2.11.1 NB-IoT Energy Eciency Challenges and opportunities
2.11.2 Data Rates enhancement and network reliability challenges
2.11.3 Network Scalability issues
2.12 Conclusion
3. A Modelling Approach of the Narrowband IoT (NB-IoT) PHY Layer Performance
3.1 Introduction
3.2 NB-IoT Operation Modes
3.3 The Downlink (DL) interface Model
3.3.1 The narrowband physical broadcast channel (NPBCH)
3.3.2 The narrowband physical downlink control channel (NPDCCH) 98
3.3.3 The narrowband physical downlink shared channel (NPDSCH) 98
3.3.4 A Prediction Model for the NB-IoT DL Processing Delay
3.3.5 The NB-IoT DL versus the LTE DL: Fundamental dierences 102
3.4 NB-IoT data rate versus energy eciency mathematical modelling and analysis
3.5 Performance analysis
3.5.1 Simulation set-up
3.5.2 Results Obtained
3.6 Conclusion
4. An Energy-Ecient and Adaptive Channel Coding Approach for Narrowband Internet of Things (NB-IoT) Systems
4.1 Introduction
4.2 Background and Motivation
4.3 Methods and Experimental Approach
4.3.1 Power Consumption Model
4.4 An Overview of Existing Energy Eciency Techniques for NB-IoT Systems
4.4.1 Existing NB-IoT Energy-Ecient Channel Coding (CC) Ap-proaches
4.4.2 Ecient Selection of Modulation Coding Scheme (MCS)
4.4.3 Repetition-Dominated Channel Coding Approaches
4.4.4 The NBLA and Its Open-Loop Power Control Approaches
4.4.5 NBLA Open-Loop Power Control
4.5 The Proposed Adaptive Channel Coding Technique
4.5.1 The Inner Loop Approach
4.5.2 The Outer Loop Link Adaptation Approach
4.6 Performance Evaluation
4.6.1 Evaluation Setup
4.6.2 EEACC MATLAB Simulation
4.6.3 Obtained Results and Discussion
4.7 Conclusion
5. A Novel Spread Spectrum and Clustering Mixed Approach with Network Coding for Enhanced Narrowband IoT (NB-IoT) Scal-ability
5.1 Introduction
5.2 Background, Motivation and Objectives
5.3 The proposed Intelligent Mixed Approach
5.3.1 Hypothesis of the proposed approach
5.3.2 The Mixed Frequency Hopping Spread Spectrum and Cluster- ing Algorithm
5.4 Performance Evaluation and Obtained Results
5.4.1 Evaluation set-up
5.4.2 Real-Life Application Scenario under Simulation
5.4.3 Obtained Results, Analysis & Discussion
5.5 Conclusion
6. Conclusions and Recommendations for future work
6.1 Introduction
6.2 The stated research objectives and achievements of the Study
6.3 Benets of the study
6.4 Recommendations for Future study
6.5 Overall Conclusions
