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Home / Books / Published Books / Self-optimization Technologies for Small Cells: Challenges and Opportunities
Self-optimization Technologies for Small Cells: Challenges and Opportunities
Authors:
Zhang Qixun, Yang Tuo, Feng Zhiyong, Wei Zhiqing
ISBN:
978-1-940366-78-4
Published Date:
October, 2017
Pages:
144
Paperback:
$100
Publisher:
Science Publishing Group
OPEN ACCESS
To purchase hard copies of this book, please email:
book@sciencepublishinggroup.com
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Table of Contents
The Whole Book
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Front Matter
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Chapter 1 Challenges and Trends for Future Wireless Networks
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1.1 Capacity Surge and Challenge in Heterogeneous Networks
1.2 Uneven Traffic Distribution in Geography and Time Domains
1.3 Advantages and Challenges of Small Cell Networks
1.3.1 Theoretical Analysis of Small Cell Capacity
1.3.2 Theoretical Analysis of Small Cell Coverage
1.3.3 Resource Allocation
1.3.4 Interference Management and Coordination
1.4 Outline Structure of This Book
Chapter 2 Capacity Improvement for Densely Deployed Small Cell Networks
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2.1 Introduction of Problems and Challenges
2.2 Capacity Analysis Using Different Frequency Allocation Schemes
2.2.1 System Model and Scenario
2.2.2 Orthogonal Frequency Allocation Scheme
2.2.3 Co-channel Frequency Allocation Scheme
2.2.4 Hybrid Frequency Allocation Scheme
2.3 Optimal Geographic Region Division Scheme for Small Cell Networks
2.3.1 Error Probability of Different Geographic Region Division Schemes
2.3.2 Optimal Geographic Region Division Scheme
2.4 Self-deployment Procedure of Hybrid Frequency Allocation Scheme
2.5 Results and Performance Analyses
2.5.1 SINR Analysis of Hybrid Frequency Allocation Scheme
2.5.2 Capacity Analysis of Hybrid Frequency Allocation Scheme
2.6 Concluding Remarks
Chapter 3 Coverage Self-optimization for Randomly Deployed Indoor Small Cell Networks
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3.1 Introduction of Problems and Challenges
3.2 Theoretical Model and Analysis on Optimal Coverage Radius
3.2.1 Optimal Coverage Radius for Center Position
3.2.2 Optimal Coverage Radius for Corner Position
3.2.3 Optimal Coverage Radius for Sidewall Midpoint Position
3.3 Optimal Power Allocation Scheme for Indoor Small Cell Networks
3.3.1 Coverage Self-optimization Scheme
3.3.2 Static Power Allocation Scheme
3.3.3 Dynamic Power Allocation Scheme
3.4 Artificial Neural Network Model Based Joint Coverage Self-optimization
3.4.1 Artificial Neural Network Model
3.4.2 ANN Based Joint Coverage Self-optimization Scheme Design
3.5 Results and Performance Analyses
3.6 Concluding Remarks
Chapter 4 Fairness Guaranteed Interference Mitigation Scheme in Multi-tier Small Cell Networks
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4.1 Introduction of Problems and Challenges
4.2 System Model and Problem Formulation in Multi-tier Small Cell Networks
4.2.1 System Model and Typical Scenario
4.2.2 Problem Formulation Using Cell Association and Resource Partitioning
4.2.3 Interference and Capacity Analysis using CRE and eICIC Technologies
4.3 Fairness Guaranteed Optimal CRE Bias and ABS Ration Solution
4.4 Results and Performance Analyses
4.4.1 Capacity Analysis of Stand-alone Effects by BS density, CRE, and eICIC
4.4.2 Optimal CRE Bias and ABS Ratio Technology
4.4.3 System-level Simulation Results of Novel eICIC Technology
4.5 Concluding Remarks
Chapter 5 Conclusion and Future Research Directions
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5.1 Concluding Remarks
5.2 Potential Future Works
Back Matter
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Author(s)
Zhang Qixun, is a member of IEEE and an associate professor with the Key Laboratory of Universal Wireless Communications, Ministry of Education. He holds B.S. and Ph.D. degrees in Information and Communication Engineering from Beijing University of Posts and Telecommunications (BUPT), Beijing, China. He is the reviewer of IEEE JSAC, IEEE TVT, IEEE ICC, Globecom, VTC, WCNC. He is active in ITU-R, IEEE, CCSA, and IMT-2020(5G) standards. His research interests include 5th generation mobile networks (5G), cognitive radio and heterogeneous networks, game theory, LAA and LTE-U system, and unmanned aerial vehicles (UAVs) communication.

Yang Tuo, is currently working towards the Master’s degree with the School of Information and Communication Engineering, Beijing University of Posts and Telecommunications (BUPT), Beijing, China. His current research interests include heterogeneous wireless networks, Markov chain model, LAA and LTE-U system.

Feng Zhiyong, is a senior member of IEEE and a full professor. She is the director of the Key Laboratory of Universal Wireless Communications, Ministry of Education. She holds B.S., M.S., and Ph.D. degrees in Information and Communication Engineering from Beijing University of Posts and Telecommunications (BUPT), Beijing, China. She is a technical advisor of NGMN, the editor of IET Communications, and KSII Transactions on Internet and Information Systems, the reviewer of IEEE TWC, IEEE TVT, and IEEE JSAC. She is active in ITU-R, IEEE, ETSI and CCSA standards. Her main research interests include wireless network architecture design and radio resource management in 5th generation mobile networks (5G), spectrum sensing and dynamic spectrum management in cognitive wireless networks, universal signal detection and identification, and network information theory.

Wei Zhiqing, a member of IEEE and an assistant professor with the Key Laboratory of Universal Wireless Communications, Ministry of Education. He holds B.S. and Ph.D. degrees in Information and Communication Engineering from Beijing University of Posts and Telecommunications (BUPT), Beijing, China. He is the reviewer of IEEE JSAC, IEEE TVT, IEEE ICC, Globecom, VTC, WCNC. His research interests include capacity and delay analysis of cognitive radio networks and 5th generation mobile networks (5G).
Description
The surge of mobile data services driven by new applications and smart devices has triggered the research innovation and study for the fifth-generation (5G) mobile communications system with a dramatic increase on system performances, such as 1 million connections per square kilometer, tens of Gbps per square kilometers of traffic volume density, and etc. To solve the capacity enhancement problem, small cells technologies have been proposed recently by reusing the spectrum resources efficiently. But, the capacity surge in urban areas and unevenly distribution of traffics in geography and time domains lead to new challenging problems for the optimization of small cell networks. Therefore, this book has proposed the capacity analysis and coverage self-optimization technologies with simulation results. And the interference mitigation technology is designed to minimize the inter-cell and intra-cell interference among multi-tier small cell networks. Finally, future research directions are described briefly.
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