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Wireless Traffic Steering For Green Cellular Networks 1st ed. 2016 [Kõva köide]

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  • Formaat: Hardback, 128 pages, kõrgus x laius: 235x155 mm, kaal: 3376 g, 41 Illustrations, color; 2 Illustrations, black and white; XI, 128 p. 43 illus., 41 illus. in color., 1 Hardback
  • Ilmumisaeg: 10-Jun-2016
  • Kirjastus: Springer International Publishing AG
  • ISBN-10: 3319327194
  • ISBN-13: 9783319327198
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Wireless Traffic Steering For Green Cellular Networks 1st ed. 2016Suurem pilt
  • Formaat: Hardback, 128 pages, kõrgus x laius: 235x155 mm, kaal: 3376 g, 41 Illustrations, color; 2 Illustrations, black and white; XI, 128 p. 43 illus., 41 illus. in color., 1 Hardback
  • Ilmumisaeg: 10-Jun-2016
  • Kirjastus: Springer International Publishing AG
  • ISBN-10: 3319327194
  • ISBN-13: 9783319327198
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9783319327198.html
Märksõnad:
This book introduces wireless traffic steering as a paradigm to realize green communication in multi-tier heterogeneous cellular networks. By matching network resources and dynamic mobile traffic demand, traffic steering helps to reduce on-grid power consumption with on-demand services provided. This book reviews existing solutions from the perspectives of energy consumption reduction and renewable energy harvesting. Specifically, it explains how traffic steering can improve energy efficiency through intelligent traffic-resource matching. Several promising traffic steering approaches for dynamic network planning and renewable energy demand-supply balancing are discussed. This book presents an energy-aware traffic steering method for networks with energy harvesting, which optimizes the traffic allocated to each cell based on the renewable energy status. Renewable energy demand-supply balancing is a key factor in energy dynamics, aimed at enhancing renewable energy sustainability to

reduce on-grid energy consumption. Dynamic network planning adjusts cell density with traffic variations to provide on-demand service, which reduces network power consumption with quality of service provisioning during off-peak hours. With intra- or inter-tier traffic steering, cell density is dynamically optimized with regards to the instant traffic load for conventional homogeneous and multi-tier heterogeneous cellular networks, respectively. This book is beneficial for researchers and graduate students interested in traffic management and future wireless networking. 

Introduction.- Literature Review on Green Communications.- Dynamic Network Planning with Intra-Tier Traffic Steering.- Dynamic Network Planning with Inter-Tier Traffic Steering.- Inter-Tier Traffic Steering with Renewable Energy Harvesting.- Concluding Remarks.
1 Introduction
1(18)
1.1 Evolution of Cellular Networks
1(3)
1.1.1 Network Capacity Enhancement
1(1)
1.1.2 Heterogeneous Network Architecture
2(1)
1.1.3 Energy Issues in Cellular Networks
3(1)
1.2 Energy Saving in Cellular Networks
4(3)
1.2.1 Energy Consumption Analysis
4(2)
1.2.2 Wireless Traffic Dynamics
6(1)
1.2.3 Traffic-Aware On-Demand Service
6(1)
1.3 Leveraging Renewable Energy
7(3)
1.3.1 Renewable Energy Powered Base Stations
7(2)
1.3.2 Traffic-Energy Mismatch
9(1)
1.4 Wireless Traffic Steering
10(5)
1.4.1 Network Heterogeneity
10(2)
1.4.2 Approaches and Benefits
12(2)
1.4.3 Applications for Green Communication
14(1)
1.5 Summary
15(4)
References
15(4)
2 Literature Review on Green Communications
19(16)
2.1 Energy Saving at Base Stations
19(6)
2.1.1 Radio Frequency Power Saving
19(1)
2.1.2 Single-BS Sleeping Control
20(2)
2.1.3 Dynamic Network Planning with Traffic Steering
22(3)
2.2 Renewable Energy Utilization
25(6)
2.2.1 Single-Link Analysis
25(2)
2.2.2 Single-BS Power Control
27(1)
2.2.3 Multi-BS Energy Cooperation
28(1)
2.2.4 Energy-Sustainable Traffic Steering
29(2)
2.3 Summary
31(4)
References
31(4)
3 Dynamic Network Planning with Intra-Tier Traffic Steering
35(22)
3.1 Network Topology and Operations
36(4)
3.1.1 Network and Traffic Models
36(1)
3.1.2 Regularly Sleeping Mechanism
36(3)
3.1.3 Problem Formulation
39(1)
3.2 Blocking Probability Analysis
40(4)
3.2.1 Link Layer Analysis
40(1)
3.2.2 Spatial Erlang-n Approximation
41(1)
3.2.3 Blocking Probability Derivation
42(2)
3.3 Energy-Optimal Network Operation
44(2)
3.3.1 Blocking Probability Evaluation
44(2)
3.3.2 Energy-Optimal Inter-Cell Distance
46(1)
3.4 Energy-Optimal Network Deployment
46(8)
3.4.1 Problem Formulation
46(3)
3.4.2 Energy-Optimal Density
49(1)
3.4.3 Resource Traffic Matching
50(2)
3.4.4 Influence of Deployment Cost
52(2)
3.5 Summary
54(3)
References
54(3)
4 Dynamic Network Planning with Inter-Tier Traffic Steering
57(34)
4.1 Network Topology and Operations
58(4)
4.1.1 Network Model
58(4)
4.1.2 Sleeping Schemes
62(1)
4.2 Quality of Service Analysis
62(14)
4.2.1 Link Layer Analysis
63(2)
4.2.2 Outage Constraint Analysis
65(9)
4.2.3 Analytical Results Evaluation
74(2)
4.3 Optimal SBS Sleeping
76(10)
4.3.1 Optimal Random Scheme
76(2)
4.3.2 Optimal Repulsive Scheme
78(4)
4.3.3 Numerical Results and Analysis
82(4)
4.4 Energy-Optimal Network Deployment
86(3)
4.4.1 Energy Consumption with Daily Traffic
86(2)
4.4.2 Optimal MBS Density
88(1)
4.5 Summary
89(2)
References
89(2)
5 Inter-Tier Traffic Steering with Renewable Energy Harvesting
91(36)
5.1 Introduction
91(1)
5.2 Heterogeneous Networks with Diverse Energy Sources
92(6)
5.2.1 Traffic Demand and Service
93(1)
5.2.2 Base Station Power Consumption
94(1)
5.2.3 Renewable Energy Supply
95(2)
5.2.4 Network Control
97(1)
5.3 QoS-Constrained Service Capability
98(8)
5.3.1 Achievable Rate Analysis
98(2)
5.3.2 Rate Outage Probability Analysis
100(6)
5.4 Local Control and Optimization
106(8)
5.4.1 Battery State Analysis
106(1)
5.4.2 Single-HSBS Analysis
107(3)
5.4.3 Single-RSBS Analysis
110(4)
5.4.4 Influence of Sleeping Power
114(1)
5.5 Global Network Control and Optimization
114(3)
5.5.1 Problem Formulation
114(2)
5.5.2 Two-Stage Traffic Steering
116(1)
5.6 Simulation Studies
117(6)
5.6.1 Outage Probability Evaluation
119(1)
5.6.2 Single-SBS Case Evaluation
120(3)
5.6.3 Multi-SBS Case Evaluation
123(1)
5.7 Summary
123(4)
References
124(3)
6 Concluding Remarks
127