Muhammad Ismail: Postdoctoral Research Associate, Electrical and Computer Engineering Department, Texas A&M University at Qatar, Doha, Qatar. Dr. Ismail’s area of expertise is related to radio resource allocation in a heterogeneous wireless medium. He is a co-recipient of the best paper award at IEEE ICC '14 for a paper related to green resource allocation in a heterogeneous wireless medium: M. Ismail, A. T. Gamage, W. Zhuang, and X. Shen, "Energy efficient uplink resource allocation in a heterogeneous wireless medium," IEEE ICC'14, (to be listed in IEEExplore).Muhammad Zeeshan Shakir: Assistant Research Scientist, Electrical and Computer Engineering Department, Texas A&M University at Qatar, Doha, Qatar. Dr. Shakir's research interests include design and deployment of diverse green wireless communication systems including hyper-dense heterogeneous small-cell networks with particular focus on traffic offloading techniques and backhauling technologies. He has published more than 50 technical journal and conference papers and has contributed to 6 books.Khalid Qaraqe: Professor, Electrical and Computer Engineering Department, Texas A&M University at Qatar, Doha, Qatar. Dr. Qaraqe has over 15 years of experience in the telecommunications industry. He has worked for Qualcomm, Enad Design Systems, Cadence Design Systems/Tality Corporation, STC, SBC and Ericsson. His research interests include communication theory and its application to design and performance analysis of cellular systems and indoor communication systems. Particular interests are in the development of 4G LTE, cognitive radio systems, broadband wireless communications and diversity techniques.Erchin Serpedin: Professor, Electrical and Computer Engineering Department, Texas A&M University, College Station, Texas, USA.  Dr. Serpedin is the author of two research monographs, one edited textbook, 100 journal papers and 180 conference papers, and has served as associate editor for approximately 12 journals including IEEE Transactions on Information Theory, IEEE Signal Processing Magazine, IEEE Transactions on Communications, and IEEE Communications Letters. His research interests include signal processing, wireless communications, computational statistics, and bioinformatics and systems biology. He is currently serving as editor in chief of the Eurasip Journal on Bioinformatics and Systems Biology, an online journal edited by Springer. He is also an IEEE Fellow.

• Preface xiAcknowledgements xiiiDedication xvPart I INTRODUCTION TO GREEN NETWORKS1 Green Network Fundamentals 31.1 Introduction: Need for Green Networks 31.2 Traffic Models 51.2.1 Traffic Spatial Fluctuation Modelling 61.2.2 Traffic Temporal Fluctuation Modelling 81.3 Energy Efficiency and Consumption Models in Wireless Networks 91.3.1 Throughput Models 91.3.2 Power Consumption Models 101.3.3 Energy Efficiency and Consumption Models 191.4 Performance Trade-Offs 231.4.1 Network-side Trade-Offs 241.4.2 Mobile User Trade-Offs 261.5 Summary 282 Green Network Solutions 292.1 Green Solutions and Analytical Models at Low and/or Bursty Call Traffic Loads 292.1.1 Dynamic Planning 292.1.2 MT Radio Interface Sleep Scheduling 342.1.3 Discussion 372.2 Green Solutions and Analytical Models at High and/or Continuous Call Traffic Loads 382.2.1 Scheduling for Single-Network Access 382.2.2 Scheduling for Multi-Homing Access 412.2.3 Scheduling with Small-Cells 412.2.4 Relaying and Device-to-Device Communications 422.2.5 Scheduling with Multiple Energy Sources 452.2.6 Discussion 472.3 Green Projects and Standards 482.4 Road Ahead 492.5 Summary 52Part II MULTI-HOMING RESOURCE ALLOCATION3 Green Multi-homing Approach 553.1 Heterogeneous Wireless Medium 553.1.1 Wireless Networks 563.1.2 Mobile Terminals 573.1.3 Radio Resources and Propagation Attenuation 573.2 Green Multi-homing Resource Allocation 583.3 Challenging Issues 603.3.1 Single-User versus Multiuser System 603.3.2 Single-Operator versus Multioperator System 603.3.3 Fairness 613.3.4 Centralized versus Decentralized Implementation 613.3.5 In-device Coexistence Interference 623.3.6 Computational Complexity 663.3.7 Number of MT Radio Interfaces versus Number of Available Networks 673.4 Summary 694 Multi-homing for a Green Downlink 704.1 Introduction 704.2 Win–Win Cooperative Green Resource Allocation 724.2.1 Non-cooperative Single-Network Solution 734.2.2 Win–Win Cooperative Solution 754.2.3 Benchmark: Sum Minimization Solution 814.2.4 Performance Evaluation 814.3 IDC Interference-Aware Green Resource Allocation 864.3.1 IDC Interference-Aware Resource Allocation Design 874.3.2 Performance Evaluation 904.4 Summary 935 Multi-homing for a Green Uplink 945.1 Introduction 945.2 Green Multi-homing Uplink Resource Allocation for Data Calls 955.2.1 Optimal Green Uplink Radio Resource Allocation with QoS Guarantee 975.2.2 Suboptimal Uplink Energy-Efficient Radio Resource Allocation 1025.2.3 Performance Evaluation 1045.3 Green Multi-homing Uplink Resource Allocation for Video Calls 1075.3.1 Energy Management Sub-system Design 1095.3.2 Performance Evaluation 1145.4 Summary 1176 Radio Frequency and Visible Light Communication Internetworking 1196.1 Introduction 1196.2 VLC Fundamentals 1206.2.1 VLC Transceivers 1206.2.2 VLC Channel 1226.2.3 Interference Issues in VLC 1246.2.4 VLC–RF Internetworking 1266.3 Green RF–VLC Internetworking 1286.3.1 Energy Efficiency Maximization 1296.3.2 Performance Evaluation 1336.3.3 Green VLC–RF Internetworking Challenging Issues 1376.4 Summary 138Part III NETWORK MANAGEMENT SOLUTIONS7 Dynamic Planning in Green Networks 1417.1 Introduction 1417.2 Dynamic Planning with Dense Small-Cell Deployment 1427.2.1 Energy-Efficient and QoS-Aware Cell Zooming 1447.2.2 Performance Evaluation 1457.3 Dynamic Planning with Cooperative Networking 1487.3.1 Optimal Resource On–Off Switching Framework 1507.3.2 Performance Evaluation 1527.4 Balanced Dynamic Planning Approach 1547.4.1 Two-Timescale Approach 1577.4.2 Performance Evaluation 1627.5 Summary 1648 Greening the Cell Edges 1668.1 Introduction 1668.1.1 Why Cell-on-Edge Deployment? 1678.1.2 Background Work 1688.2 Two-Tier Small-Cell-on-Edge Deployment 1698.2.1 Network Layout 1698.2.2 Bandwidth Partition and Channel Allocation 1708.2.3 Mobile User Distribution 1718.3 Energy-Aware Transmission Design 1718.3.1 Path-Loss Model for Strong LOS Conditions 1718.3.2 Composite Fading Channel for Strong LOS Conditions 1728.4 Area Spectral Efficiency of HetNets 1738.5 Analytical Bounds on ASE of HetNets 1768.5.1 Mean Achievable Capacity Based on MGF Approach 1768.5.2 Assumptions to Derive Upper and Lower Bounds 1778.5.3 Analytical Bounds on the Capacity of Macro-cell Network 1798.5.4 Analytical Bounds on the Capacity of Small-Cell Networks 1808.6 Analytical Bounds on ASE over Generalized-K Fading Channel 1818.7 Energy Analysis of HetNets 1838.7.1 Energy Consumption of Two-Tier HetNets 1848.7.2 Energy Savings of Two-Tier HetNets 1848.8 Ecology and Economics of HetNets 1858.8.1 CO2e Emissions and Reduction in CO2e Emissions 1868.8.2 Daily CO2e Emissions Profile 1868.8.3 Low-Carbon Economy 1868.9 Summary 188Appendix A - Simulation Parameters 189Appendix B - Proof of (8.38) 1899 D2D Communications in Hierarchical HetNets 1919.1 Introduction 1919.2 Modelling Hierarchical Heterogeneous Networks 1929.2.1 Network Architecture 1939.2.2 D2D User Density in Hierarchical HetNets 1949.2.3 Spectrum Partitioning in Hierarchical HetNets 1969.2.4 Power Control over D2D Links 1969.3 Spectral Efficiency Analysis 1979.3.1 Traditional HetNet 1979.3.2 Hierarchical HetNet 1989.4 Average User Transmission Power Analysis 2009.4.1 Discussion on Transmission Power Analysis of D2D Users 2029.5 Backhaul Energy Analysis 2049.5.1 Backhaul Power Consumption 2049.5.2 Backhaul Energy Efficiency 2059.5.3 Considerations on Backhaul Energy Efficiency of Hierarchical HetNet 2069.6 Summary 208Appendix A 209Appendix B - Simulation Parameters 21010 Emerging Device-Centric Communications 21110.1 Introduction 21110.2 Emerging Device-Centric Paradigms 21210.2.1 Device-to-Device Communication Management 21310.2.2 Device-to-Device Communication Architecture 21310.2.3 Device-to-Device Communication Challenges 21410.3 Devices-to-Device Communications 21410.3.1 System Model 21410.4 Optimal Selection of Source Devices and Radio Interfaces 21610.4.1 Device Selection Criteria 21710.4.2 Ascending Proxy Auction for Device Selection 21810.4.3 Discussions on Device and Radio Interface Selection 21910.5 Optimal Packet Split among Devices 22110.6 Green Analysis of Mobile Devices 22410.6.1 Energy Consumption of Mobile Devices 22510.6.2 Electricity Cost for Mobile Charging 22610.6.3 Battery Life of Mobile Devices 22710.7 Some Challenges and Future Directions 22810.7.1 Centralized Ds2D Set-up 22810.7.2 Decentralized Ds2D Set-up 22810.8 Summary 229References 230Index 245