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.

• 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