Virtualized Base Station Resource Scaling for Real-Time UE Demand
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Solution Overview
Problem
Conventional fixed maximum network resource allocation in telecommunication networks leads to inefficiencies and increased energy consumption, particularly with next-generation applications like extended reality (XR) services, and existing virtualized base station technologies suffer from temporal gaps in resource allocation, impairing the network's ability to meet user service requirements in real-time.
Innovation Solution
A network management system with a processor, storage medium, and transceiver that includes modules for monitoring, UE information handling, scaling configuration, and vRAN management, dynamically adjusts reserved resources of virtualized base stations based on UE location and resource requirements, using a UE information table to categorize UEs and predict future resource needs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If fixed maximum network resource allocation is used, then user service requirements are fulfilled, but energy consumption increases and resource allocation efficiency deteriorates
Solution Approach 1:
The patent implements dynamic resource allocation by continuously monitoring UE location information and resource requirements, then adjusting reserved resources for virtualized base stations in real-time. The system transitions from fixed maximum allocation to dynamic adjustment based on actual demand, reducing energy consumption while maintaining service reliability.
Solution Approach 2:
The system changes the allocation parameter from a static fixed maximum value to a dynamic value that varies based on UE location and resource requirements. The network management system adjusts the reserved resource parameters of virtualized base stations according to real-time conditions, optimizing the balance between service fulfillment and energy efficiency.
2Productivity
If virtualized base station resource allocation is implemented, then network resource allocation efficiency improves, but a temporal gap is introduced that impairs real-time resource allocation capability
Solution Approach 1:
The system performs preliminary actions by proactively monitoring UE location information and resource requirements before actual resource allocation is needed. The network management system predicts future resource needs and adjusts reservations in advance, eliminating temporal gaps and enabling real-time response to changing network conditions.
Solution Approach 2:
The patent implements a feedback mechanism where the network management system continuously monitors UE location and resource requirements, compares this information with current virtualized base station reservations, and adjusts allocations in real-time. This closed-loop feedback eliminates temporal gaps by ensuring resource allocation keeps pace with dynamic network demands.
3Loss of energy
If resource allocation is adjusted dynamically, then energy efficiency improves, but the complexity of the network management system increases
Solution Approach 1:
The system enables self-service by having the network management system automatically monitor UE location information, query resource requirements, and adjust virtualized base station reservations without manual intervention. The automated feedback loop handles the complexity internally, presenting a simple external interface while reducing energy efficiency through dynamic optimization.
Data Source
AI summary
A network management system and a method of automatic adjustment for a virtualized base station are provided. The method includes following steps. A user equipment (UE) information table is queried from a core network, and a first reserved resource of a first virtualized base station is queried, where the UE information table includes first location information and a first resource requirement corresponding to a first UE set. A second resource requirement corresponding to a second UE set is obtained from the UE information table based on the first location information and a default range. Whether the first reserved resource matches the second resource requirement is determined to generate a determination result. The first reserved resource of the first virtualized base station is expanded or reduced based on the determination result.