Shared RAN Energy Scheduling for Multi-Operator QoS Control
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Solution Overview
Problem
The increasing power consumption in advanced communication networks, particularly in 5G and beyond, due to network densification and complex data processing, poses challenges for network efficiency and cost-effectiveness, with conventional energy-saving methods in shared RAN architectures being inadequate for managing multi-operator scenarios.
Innovation Solution
A hierarchical deep reinforcement learning (DRL) approach is employed to optimize energy efficiency in shared radio access networks (RANs) by implementing energy-efficient scheduling and network energy savings actions, leveraging intra- and inter-network operator loops, and utilizing data-driven optimization to reduce global energy metrics while maintaining quality of service levels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If network densification and complex data processing are implemented to meet explosive demand for mobile networks, then network data rate and processing capability are improved, but power consumption increases exponentially
Solution Approach 1:
The patent segments the RAN into multiple shared cells that can be dynamically allocated to different network operators. By dividing the network infrastructure into manageable units that can be independently controlled and shared, the system achieves better resource utilization and energy efficiency while maintaining high data rates for multiple operators simultaneously
Solution Approach 2:
The patent implements a universal shared RAN infrastructure that serves multiple network operators with different requirements. The same physical network resources (cells, base stations) perform multiple functions for different operators, reducing overall power consumption compared to dedicated networks while maintaining the productivity needed by each operator
2Loss of energy
If conventional energy-saving methods are used in shared RAN architectures, then some power reduction is achieved, but they are inadequate for managing multi-operator scenarios with different network policies
Solution Approach 1:
The patent implements dynamic energy-saving methods that can adapt in real-time to different operator policies and network conditions. The system dynamically adjusts resource allocation, cell activation, and power consumption levels based on current traffic demands and operator-specific requirements, making conventional static methods inadequate
Solution Approach 2:
The patent changes key operational parameters such as cell power levels, resource allocation ratios, and activation thresholds based on operator policies and network conditions. This parameter-based control enables flexible energy management that adapts to multi-operator scenarios while achieving significant power reduction
3Ease of manufacture
If radio access network hardware is shared among multiple network operators, then deployment cost is reduced, but managing energy efficiency becomes more complex
Solution Approach 1:
The patent introduces an intermediary energy management system that coordinates between multiple operators sharing the same RAN hardware. This intermediary layer handles the complexity of energy management by implementing centralized control, policy enforcement, and resource allocation, simplifying the overall system while enabling cost-effective shared deployment
Data Source
AI summary
Facilitating Multiple-Tenant Energy Efficient Radio Access Network Sharing In Advanced Communication Networks is provided. A method includes facilitating, by a system comprising at least one processor, network energy savings in a communications network that is deployed in a shared radio access network architecture. The facilitating includes implementing, at a network operator level of the communications network according to a defined energy efficiency criterion, energy efficient scheduling of user equipment within the communications network. The facilitating also includes implementing, at an infrastructure provider level of the communications network, network energy savings actions based on respective measured quality of service levels of the user equipment being retained at or above a defined quality of service level. In an example, network equipment comprised by the communications network is configured to operate according to at least a fifth generation radio network communication protocol.