Green 5G: 5G's energy-saving strategies
This report analyses the ways in which environmental concerns are being factored into 5G rollouts.
It is highly likely that 5G will drive an increase in networks’ consumption, as it enables a growing number of uses, employs new frequency bands and requires increased network density, moving beyond the confines of classic broadband.
That said, a host of initiatives are focused on optimising per-unit consumption levels. This report takes a look at a number of solutions designed to reduce and optimise energy consumption (AI, sleep modes, virtualisation, etc.).
The world’s leading telecom manufacturers, equipment suppliers and operators are working to adopt these energy-saving solutions which, more and more, are being seen as selling points.
This report examines the strategies of some 20 market players, providing a detailed analysis for ten of them.
The report answers the following questions:
It is highly likely that 5G will drive an increase in networks’ consumption, as it enables a growing number of uses, employs new frequency bands and requires increased network density, moving beyond the confines of classic broadband.
That said, a host of initiatives are focused on optimising per-unit consumption levels. This report takes a look at a number of solutions designed to reduce and optimise energy consumption (AI, sleep modes, virtualisation, etc.).
The world’s leading telecom manufacturers, equipment suppliers and operators are working to adopt these energy-saving solutions which, more and more, are being seen as selling points.
This report examines the strategies of some 20 market players, providing a detailed analysis for ten of them.
The report answers the following questions:
- How will 5G change network consumption?
- What are the main (current and future) avenues for reducing 5G’s consumption?
- How are equipment suppliers tackling energy saving issues?
- Which operators have the greenest strategic plans and most ambitious carbon-neutrality targets?
1. EXECUTIVE SUMMARY
2. FACTORS BEHIND MOBILE NETWORKS’ INCREASED CONSUMPTION
2.1. Introduction
2.2. Traffic surging on all fronts
2.3. Network topologies highly influenced by spectrum
2.4. Increased network density, key to mapping the rise in consumption
2.5. Core network also affected by increased density
2.6. Development of Massive MIMO
2.7. More transmission sources means more consumption
2.8. 5G performances driving increased energy consumption
3. ENERGY SAVINGS AND OPTIMISATION SOLUTIONS
3.1. Summary: main paths to reducing energy consumption
3.2. Base stations’ advanced sleep modes
3.3. Reducing massive MIMO systems’ energy consumption
3.4. Role of AI (Machine Learning) in energy saving
3.5. Progress in semiconductors and optimising existing systems
3.6. Replacing old networks’ (2G/3G/4G) equipment
3.7. Flexible spectrum sharing for an efficient transition to 4G/5G
3.8. Access network virtualisation and resource sharing
4. PLAYERS’ POSITIONING
4.1. Summary: equipment suppliers’ positioning
4.2. Comparison of equipment suppliers’ approach to energy savings
Huawei
Nokia
Ericsson
Samsung
4.3. Summary: operators’ positioning
4.4. How players are positioned on energy consumption.
AT&T
China Mobile
Telef?nica
Vodafone
2. FACTORS BEHIND MOBILE NETWORKS’ INCREASED CONSUMPTION
2.1. Introduction
2.2. Traffic surging on all fronts
2.3. Network topologies highly influenced by spectrum
2.4. Increased network density, key to mapping the rise in consumption
2.5. Core network also affected by increased density
2.6. Development of Massive MIMO
2.7. More transmission sources means more consumption
2.8. 5G performances driving increased energy consumption
3. ENERGY SAVINGS AND OPTIMISATION SOLUTIONS
3.1. Summary: main paths to reducing energy consumption
3.2. Base stations’ advanced sleep modes
3.3. Reducing massive MIMO systems’ energy consumption
3.4. Role of AI (Machine Learning) in energy saving
3.5. Progress in semiconductors and optimising existing systems
3.6. Replacing old networks’ (2G/3G/4G) equipment
3.7. Flexible spectrum sharing for an efficient transition to 4G/5G
3.8. Access network virtualisation and resource sharing
4. PLAYERS’ POSITIONING
4.1. Summary: equipment suppliers’ positioning
4.2. Comparison of equipment suppliers’ approach to energy savings
Huawei
Nokia
Ericsson
Samsung
4.3. Summary: operators’ positioning
4.4. How players are positioned on energy consumption.
AT&T
China Mobile
Telef?nica
Vodafone
LIST OF TABLES AND FIGURES
Factors behind mobile networks’ increased consumption
Networks’ energy consumption curve and future scenarios
Breakdown of a mobile networks’ sources of energy consumption
5G target performances (IMT-2020)
Forecast increase in monthly mobile traffic worldwide
Main pros and cons of the different frequency bands
How calling networks have evolved to accommodate more complex and demanding uses
The core network’s evolution
Comparison of cell vs. massive MIMO coverage
Progression of MIMO antenna configurations and associated power needs
Key principles of 5G and how they effect the networks’ energy consumption
Energy savings and optimisation solutions
Main paths to reducing a network’s energy consumption
Sleep modes defined in 5G standards
Implementing an AI-based energy savings mechanism
Snapshot of equipment suppliers’ solutions using AI to manage sleep modes
Progression of the size of a 5G base station over the course of its development cycle
Example of a typical evolution in the different radio technologies frequency bands use
Comparison of virtualised and non-virtualised radio access network architecture
How players are positioned
Comparison of how the main equipment suppliers are positioned with respect energy efficiency
Evolution of Huawei’s active antenna solutions
Ericsson’s different energy-saving features
Measures being taken by operators to limit energy consumption
How operators are position on energy consumption
Progression of energy consumption (in GWh) by fixed and mobile networks
Difference between the two 5G services launched by AT&T and impact on network density
Progression of energy consumption (in GWh) by AT&T fixed and mobile networks
Coordinated deactivation of frequency bands according to traffic helps reduce electricity consumption
When traffic is multiplied by 3.5 over consumption remains stable
Distribution of energy savings across the network
Evolution of the Vodafone network’s energy consumption
Factors behind mobile networks’ increased consumption
Networks’ energy consumption curve and future scenarios
Breakdown of a mobile networks’ sources of energy consumption
5G target performances (IMT-2020)
Forecast increase in monthly mobile traffic worldwide
Main pros and cons of the different frequency bands
How calling networks have evolved to accommodate more complex and demanding uses
The core network’s evolution
Comparison of cell vs. massive MIMO coverage
Progression of MIMO antenna configurations and associated power needs
Key principles of 5G and how they effect the networks’ energy consumption
Energy savings and optimisation solutions
Main paths to reducing a network’s energy consumption
Sleep modes defined in 5G standards
Implementing an AI-based energy savings mechanism
Snapshot of equipment suppliers’ solutions using AI to manage sleep modes
Progression of the size of a 5G base station over the course of its development cycle
Example of a typical evolution in the different radio technologies frequency bands use
Comparison of virtualised and non-virtualised radio access network architecture
How players are positioned
Comparison of how the main equipment suppliers are positioned with respect energy efficiency
Evolution of Huawei’s active antenna solutions
Ericsson’s different energy-saving features
Measures being taken by operators to limit energy consumption
How operators are position on energy consumption
Progression of energy consumption (in GWh) by fixed and mobile networks
Difference between the two 5G services launched by AT&T and impact on network density
Progression of energy consumption (in GWh) by AT&T fixed and mobile networks
Coordinated deactivation of frequency bands according to traffic helps reduce electricity consumption
When traffic is multiplied by 3.5 over consumption remains stable
Distribution of energy savings across the network
Evolution of the Vodafone network’s energy consumption
