Network Energy Saving Using Device- and User-Level Control
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Solution Overview
Problem
Existing network energy-saving technologies primarily focus on local optimization within the core and access networks, lacking centralized control and user preference integration, leading to suboptimal energy consumption in end-to-end systems and failing to meet refined energy-saving requirements.
Innovation Solution
A network energy-saving method that obtains user and group preference information to generate device-level and user-level instructions, optimizing energy consumption by adjusting network configurations and resource allocation based on individual and collective preferences, enabling centralized control across the end-to-end system.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If local optimization methods are used within core and access networks, then energy consumption of individual network components is reduced, but overall end-to-end system energy consumption remains suboptimal
Solution Approach 1:
The patent segments the energy-saving optimization into two distinct levels: device-level optimization for individual network components (base stations, core network elements) and user-level optimization for specific user equipment. This segmentation allows simultaneous local optimization at device level while coordinating overall system optimization at user level, resolving the contradiction between component-level and system-level energy efficiency.
Solution Approach 2:
The patent introduces an energy-saving management function as an intermediary layer that coordinates between device-level optimizations and user-level requirements. This intermediary collects user preference information, generates appropriate energy-saving instructions, and mediates between network device capabilities and user needs, achieving end-to-end energy optimization that neither local optimization alone can accomplish.
2Loss of energy
If traditional energy-saving methods are applied without user preference integration, then network-wide energy reduction is achieved, but refined energy-saving requirements of individual users are not met
Solution Approach 1:
The patent applies local quality by allowing different energy-saving strategies for different users based on their individual preferences and requirements. Instead of uniform network-wide optimization, each user receives customized energy-saving instructions tailored to their specific needs, service types, and mobility patterns, enabling both network-wide energy reduction and individualized preference adaptation.
Solution Approach 2:
The patent makes the energy-saving system dynamic by continuously adapting to changing user preferences, service requirements, and network conditions. The energy-saving management function dynamically generates instructions based on real-time user feedback and preference information, allowing the system to flexibly adjust between energy-saving modes and service quality modes according to actual needs.
3Loss of energy
If device-level energy-saving instructions are generated without user-level considerations, then network device energy consumption is reduced, but user-specific energy-saving optimization is lost
Solution Approach 1:
The patent segments energy-saving optimization into device-level and user-level instructions that work together. Device-level instructions optimize network infrastructure energy consumption, while user-level instructions provide fine-grained optimization for individual user equipment. This dual-level segmentation achieves both macroscopic device energy reduction and microscopic user-specific precision optimization.
Solution Approach 2:
The patent adds a new dimension to energy-saving optimization by introducing user-level granularity alongside device-level control. Instead of only device-centric optimization, the system operates in two dimensions: network device energy management and user equipment energy management, enabling precise energy-saving at multiple levels simultaneously.
Data Source
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AI summary
A network energy-saving method, an apparatus and a storage medium are provided. The method includes: obtaining first energy-saving preference information and/or second energy-saving preference information; wherein the first energy-saving preference information represents network preference information of a target terminal; the second energy-saving preference information represents network preference information of a terminal group; generating a device-level energy-saving instruction and/or a user-level energy-saving instruction based on the first energy-saving preference information and/or the second energy-saving preference information; sending the device-level energy-saving instruction and/or the user-level energy-saving instruction to a target network; wherein the device-level energy-saving instruction and/or the user-level energy-saving instruction are received by the target network and used to perform an energy-saving optimization operation; the target network comprises a core network and/or an access network.