Cellular Network Capacity Planning for Predicting E2E Resource Breaks
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Solution Overview
Problem
5G NR cellular networks face inefficiencies in resource utilization, leading to potential breaks in end-to-end data transmission and compromised performance.
Innovation Solution
Implementing an end-to-end (E2E) network resource planning mechanism that identifies and predicts capacity metrics for network elements, allowing for proactive adjustments to avoid resource breaks through actions like adjusting memory, storage, CPU, or bandwidth.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If decentralized network architecture is used, then network flexibility and scalability are improved, but end-to-end resource coordination becomes difficult leading to capacity breaks
Solution Approach 1:
The patent implements a feedback mechanism where the E2E resource planning manager continuously monitors capacity metrics from network elements and adjusts resource allocation accordingly. This closed-loop approach ensures that the decentralized network architecture maintains end-to-end reliability by coordinating resource changes across multiple network elements based on real-time capacity information.
Solution Approach 2:
The patent performs preliminary resource planning and capacity assessment before actual data transmission occurs. The E2E resource planning manager proactively identifies potential capacity constraints and adjusts resource allocation in advance, preventing breakage before it occurs. This includes predicting future capacity needs and pre-configuring network elements accordingly.
2Reliability
If network resources are over-provisioned to prevent capacity breaks, then transmission reliability is improved, but resource utilization efficiency deteriorates
Solution Approach 1:
The patent implements dynamic resource allocation where network resources are adjusted in real-time based on actual capacity metrics and demand conditions. Rather than static over-provisioning, the system continuously monitors capacity utilization and dynamically adjusts resource allocation to match actual needs, optimizing both reliability and efficiency.
Solution Approach 2:
The patent changes key capacity parameters (such as buffer sizes, transmission rates, and resource allocation ratios) based on monitored capacity metrics. By adjusting these parameters dynamically according to actual network conditions, the system achieves reliable transmission without excessive resource provisioning, thereby improving utilization efficiency.
3Reliability
If capacity metrics are monitored continuously, then capacity issues are identified early, but system complexity and measurement overhead increase
Solution Approach 1:
The patent segments the monitoring function into discrete capacity metrics that can be independently collected and processed from different network elements. The E2E resource planning manager collects specific capacity parameters (such as buffer utilization, transmission rate, error rates) from individual network elements, allowing for targeted monitoring that reduces overall system complexity while maintaining detection accuracy.
Data Source
AI summary
Technologies for end-to-end (E2E) network resource planning in a cellular network are described. One method include identifying a plurality of network elements in the cellular network; identifying a capacity metric associated with each network element of the plurality of network elements; determining a threshold criterion of the capacity metric for each network element of the plurality of network elements; and predicting a timepoint of a breakage associated with each network element of the plurality of network elements, wherein the breakage occurs responsive to a capacity metric satisfies a corresponding threshold criterion.