5G Networks
Planning, Design and Optimization
- 1st Edition - August 20, 2018
- Author: Christofer Larsson
- Language: English
5G Networks: Planning, Design and Optimization presents practical methods and algorithms for the design of 5G Networks, covering issues ranging from network resilience to how Big D… Read more
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Description
Description
5G Networks: Planning, Design and Optimization presents practical methods and algorithms for the design of 5G Networks, covering issues ranging from network resilience to how Big Data analytics can used in network design optimization. The book addresses 5G optimization issues that are data driven, high dimensional and clustered.
The reader will learn:
- 5G concepts, how they are linked and their effect on the architecture of a 5G network
- Models of 5G at a network level, including economic aspects of operating a network
- The economic implications of scale and service diversity, and the incentive for optimal design and operational strategies
- Network topologies from a transport to a cloud perspective
- Theoretic foundations for network design and network optimization
- Algorithms for practical design and optimization of 5G subsystems based on live network projects
- Efficient Bayesian methods for network analytics
- The trade-off and multi-objective character of QoS management and cost saving
- Practical traffic and resilience measurement and QoS supervision
- Frameworks for performance analytics and network control
This book will be an invaluable resource for telecom operators and service providers, university researchers, graduate students and network planners interested in practical methods for optimizing networks for large performance improvements and cost savings.
Christofer Larsson works as an independent researcher and consultant in network design traffic engineering, network performance evaluation and optimization.
Key features
Key features
- 5G concepts, how they are linked and their effect on the architecture of a 5G network
- Models of 5G at a network level, including economic aspects of operating a network
- The economic implications of scale and service diversity, and the incentive for optimal design and operational strategies
- Network topologies from a transport to a cloud perspective
- Theoretic foundations for network design and network optimization
- Algorithms for practical design and optimization of 5G subsystems based on live network projects
- Efficient Bayesian methods for network analytics
- The trade-off and multi-objective character of QoS management and cost saving
- Practical traffic and resilience measurement and QoS supervision
- Frameworks for performance analytics and network control
Readership
Readership
Table of contents
Table of contents
Chapter 1. Concepts and Architectures in 5G
Network Function Virtualization (NFV)
Software Defined Networks (SDN)
Cloudification
Heterogeneous networks
Internet of Things (IoT)
Use Cases, Smart grids, cities and homes
Big Data, Causes and implications
Traffic self-similarity and long-range dependence
Security and Integrity Protection
Optimization problems in 5G
Chapter 2. Clustering Techniques
The use of clustering in design, optimization and data analysis; Complexity
Cluster properties. Cluster quality measures: Performance, conductance and expansion
Heuristic methods clustering
k-Nearest Neighbor
k-Means and k-Median
Spectral clustering
Iterative improvement
Chapter 3 Facility Location and Assignment
The facility location problem: Heuristic methods; A primal-dual algorithm
Assignment and transportation problems, matching; Heuristic methods and approximations;
Metaheuristics: Genetic Algorithms, Ant Colony Optimization
Scheduling
Chapter 4. Network Access
General access, hierarchical networks; Aggreation, and last mile access
Radio enhancing features; Self-Optimizing Networks (SON); Massive MIMO
Capacitated minimum spanning trees: The algorithms by Essau-Williams and Sharma
Steiner trees and stainer connectivity; Heuristic methods; The Dreifus-Wagner algorithm; The Robins-Zelikovsky algorithm
Resilience in Radio Access Networks. A genetic algorithm for resilience improvement
Centralized RAN (C-RAN), Location of baseband hotels, Maximization of radio network efficiency
Chapter 5. Resilience and Optimal Routing
Measuring resilience; Resilience as a network resource; Rare events
N-k survivable networks, Bender's decomposition
Steiner connectivity
Simulating and estimating resilience
Virtual Private Networks (VPNs)
Resilient routing
Multipath Label Switching (MPLS), The k-Shortest Path, Resilient routing of different traffic classes
Software Defined WAN (SD-WAN)
Chapter 6. Datacenters and Clouds
Anything-as-a-Service (XaaS)
Cost, resilience and optimality in cloud engineering
Load balancing and assignment
Optimal assignment of virtual machines; An algorithm based on Ant Colony Optimization
Optimal job scheduling
Software Tools: CloudSim
Chapter 7. Self-Similar and Long-Range Dependent Traffic
Self-similarity and long-range dependence
Causes and effects on latency and jitter
Detection of long-range dependence and self-similarity
Wavelet analysis and simulation of self-similar traffic.
The FARIMA and fractional Brownian motion models, analysis and forecasting
Buffer sizing and traffic prioritization
Chapter 8. Analytics and Big Data in 5G
Generation of Big Data: data sources
Data consistency and integrity
Machine Learning techniques
Approximate Bayesian Computation
Metropolis-Hastings and the Gibbs sampler
Analytics for network Key Performance Indicators
Monitoring of Quality of Service
Data mining for network management: fault management, performance management and configuration management
Chapter 9. Network and Service Control
Smart grids, cities and homes; Policies and control
Stochastic optimal control and its applications
Filtering and forecasting
Inverse problems, Regularization
Quality of Service enforcement
Markovian control
Dynamic programming
+Chapter 10. Network Slicing
Use Cases and Service Level Agreements (SLA); Examples of Massive and critical services
Orchestration: Fairness, SLA enforcement and cost optimization; Resource allocation on different time scales
Multi-objective optimization: QoS and cost for use cases
Mobility models
Resource allocation; Two-step resource optimization: static and dynamic resource mapping
Monitoring of performance and QoS, and control of network slices
Product details
Product details
- Edition: 1
- Published: August 23, 2018
- Language: English
About the author
About the author
CL
Christofer Larsson
Christofer Larsson, an Engineering Physics graduate of the Royal Institute of Technology in Stockholm, Sweden, is a consultant in network design and optimization, and a textbook author. Taking a strong interest in engineering mathematics, Christofer has during three decades in IT and telecommunications participated in the design and implementation of several successful innovative network solutions. Christofer has held positions as system designer, software architect, tester, trainer, technical writer, and manager. After a decade with Ericsson, he has been a consulting partner with system vendors, network operators and software providers, including Ericsson, NSN, Siemens, Deutsche Telekom, Vodafone-Hutchinson, and Orange