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Efficient integration of 5G and beyond heterogeneous networks / Zi-Yang Wu, Muhammad Ismail, Justin Kong, Erchin Serpedin, Jiao Wang.

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This book discusses the smooth integration of optical and RF networks in 5G and beyond (5G+) heterogeneous networks (HetNets), covering both planning and operational aspects. The integration of high-frequency air interfaces into 5G+ wireless networks can relieve the congested radio frequency (RF) ba...

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Bibliographic Details
Online Access: Full Text (via Skillsoft)
Main Author: Wu, Zi-Yang
Other Authors: Ismail, Muhammad, 1985-, Kong, Justin, Serpedin, Erchin, 1967-, Wang, Jiao
Format: Electronic eBook
Language:English
Published: Singapore : Springer, 2020.
Subjects:
5G mobile communication systems.
Electrical engineering.
Wireless communication systems.
5G mobile communication systems
Electrical engineering
Wireless communication systems
Table of Contents:
  • Intro
  • Preface
  • Contents
  • Abbreviations
  • 1 Introduction: Challenges in 5G+HetNet Integration
  • 1.1 Wireless Medium in 5G+ HetNets
  • 1.2 Challenges in HetNet Planning
  • 1.3 Challenges in HetNet Operation
  • 1.3.1 Intelligent Handovers
  • 1.3.2 Channel Event Prediction
  • 1.3.3 Data-Driven Optimization
  • 1.3.4 Intelligent Multi-homing Support
  • 1.4 The Road Ahead
  • References
  • 2 Efficient Joint Planning of 5G+ HetNets
  • 2.1 Introduction
  • 2.1.1 Background
  • 2.1.2 Chapter Organization
  • 2.2 Network Model and Problem Formulation
  • 2.2.1 Area Power Consumption
  • 2.2.2 Preliminaries on Outage Probability of RF Networks
  • 2.2.3 Outage Probability of VLC Networks
  • 2.2.4 Problem Formulation
  • 2.3 Outage Probability of VLC Network
  • 2.4 Network Deployment
  • 2.4.1 Deployment of VLC Network
  • 2.4.2 Deployment of RF-Optical HetNet
  • 2.5 Simulation Results
  • 2.6 Summary
  • References
  • 3 Realization and Dataset Generation for Mobile Indoor Channels
  • 3.1 Introduction
  • 3.1.1 Background
  • 3.1.2 Chapter Organization
  • 3.2 Mobility Model
  • 3.2.1 Macro Patterns
  • 3.2.2 Micro Patterns
  • 3.3 Generation of Mobile Channel Data
  • 3.4 System Setup
  • 3.4.1 Measurement Setup
  • 3.4.2 Synthetic Setup
  • 3.5 Channel Characterization
  • 3.5.1 Overall Statistics
  • 3.5.2 Spatial Features
  • 3.5.3 Temporal Features
  • 3.5.4 Handover Rate
  • 3.6 Summary
  • References
  • 4 Data-driven Handover Framework in Mobile 5G+ HetNets
  • 4.1 Introduction
  • 4.1.1 Background
  • 4.1.2 Chapter Organization
  • 4.2 Indoor Layout and Network Model
  • 4.2.1 Achieved Throughput in RF Channels
  • 4.2.2 Achieved Throughput in Optical Channels
  • 4.3 Handover Problem Definition
  • 4.3.1 Objective Metric
  • 4.3.2 Problem Statement
  • 4.3.3 Overview of Smart Handover Framework
  • 4.4 Channel Event Predictor
  • 4.4.1 Prediction Problem Definition
  • 4.4.2 Event Prediction Under Sparsity of Channel Gain
  • 4.4.3 Event Abstraction and Data Densification
  • 4.4.4 Event Regression
  • 4.4.5 Event Sparsification
  • 4.5 QoS-Guaranteed Handover Assignment
  • 4.5.1 Definition of States
  • 4.5.2 Definition of Actions
  • 4.5.3 Definition of Rewards
  • 4.5.4 Q-learning-based Handover Policy
  • 4.6 Numerical Results and Discussions
  • 4.6.1 Parameter Setup
  • 4.6.2 Prediction Interval
  • 4.6.3 Prediction Performance
  • 4.6.4 Trace Information
  • 4.6.5 Handover Assignment
  • 4.6.6 Complexity
  • 4.7 Summary
  • References
  • 5 Data-Driven Multi-homing Resource Allocation in Mobile 5G+ HetNets
  • 5.1 Introduction
  • 5.1.1 Background
  • 5.1.2 Chapter Organization
  • 5.2 Network Model and Problem Formulation
  • 5.3 Two-Timescale Power Allocation
  • 5.3.1 Definitions of State, Action and Cost
  • 5.3.2 Multi-agent Q-learning-based Power Allocation
  • 5.3.3 Complexity
  • 5.4 Numerical Results
  • 5.5 Summary
  • References
  • 6 Conclusions
  • 6.1 Summary
  • 6.1.1 Holistic Joint Planning Strategy for 5G+ HetNets

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