Front-Haul Network Resource Control via Real-Time Feedback
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Solution Overview
Problem
Current front-haul network management in cloud-RAN architecture is unable to stabilize network resources in real-time due to inaccurate predictive control, leading to instability from unexpected temporal events and varying user equipment load.
Innovation Solution
Implementing a method and apparatus that collect and manage front-haul network characteristics, such as capacity and bit-rate usage, to enable real-time scheduling and admission control, using a scheduler and admission controller to optimize resource allocation and stability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Force
If predictive control is used to manage front-haul network resources, then resource allocation can be planned in advance, but network stability deteriorates due to inaccurate predictions from unexpected temporal events and varying user equipment load
Solution Approach 1:
The patent implements a feedback mechanism where the scheduler receives front-haul network characteristics (capacity, bit-rate usage) from the front-haul network and uses this real-time information to adjust scheduling decisions. This closed-loop feedback system allows the network to adapt to actual conditions rather than relying solely on inaccurate predictive models, thereby maintaining network stability while still enabling proactive resource management.
Solution Approach 2:
The patent makes the scheduling system dynamic by continuously adapting scheduling decisions based on real-time front-haul network characteristics. Instead of static predictive control, the scheduler dynamically adjusts resource allocation, admission control, and scheduling parameters according to current network status, allowing the system to respond flexibly to unexpected temporal events and varying user equipment load.
2Productivity
If real-time scheduling and admission control are implemented, then network resource management improves, but system complexity increases due to the need for continuous monitoring and coordination
Solution Approach 1:
The patent implements a multi-functional scheduler that performs both scheduling and admission control functions within a single unified entity. This universal approach consolidates multiple control functions that would otherwise require separate complex systems, reducing overall system complexity while maintaining real-time resource management capabilities. The scheduler receives front-haul network characteristics and uses them for both admission decisions and resource allocation, eliminating the need for separate monitoring and control systems.
3Measurement precision
If front-haul network characteristics are continuously monitored, then resource allocation accuracy improves, but information processing load increases
Solution Approach 1:
The patent extracts only the essential front-haul network characteristics (capacity and bit-rate usage) that are most critical for scheduling decisions, rather than monitoring and processing all possible network parameters. This selective extraction approach maintains resource allocation accuracy by focusing on the most impactful metrics while significantly reducing the information processing load and energy consumption associated with continuous network monitoring.
Data Source
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AI summary
There is provided methods and apparatuses for managing front-haul network resources based on one or more front-haul network characteristics. One or more front-haul network characteristics are at least one of collected and determined by one or more front-haul network entities and are delivered to one or more network entities that manage front-haul network resources (e.g. scheduler, admission controller). The network entities, based on the received one or more front-haul network characteristics, manage network resources in their control. For example, management of the network resources can include scheduling use of the network resources by UEs, managing admission of UEs onto the communication network or other form of network resource management. By taking into account one or more front-haul network characteristics, the management of the network resources can be adapted to varying front-haul network requirements.