5G Data Transport Management for Latency-Sensitive Applications
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Solution Overview
Problem
Current cellular wireless networks face challenges in managing data transport across multiple radio frequency links for 5G-capable wireless devices, particularly in ensuring consistent data throughput and low latency for latency-sensitive applications as the device moves across varying signal conditions.
Innovation Solution
A 5G-capable wireless device can manage data transport by requesting radio resources via a master cell group (MCG) when performance via a secondary cell group (SCG) is inadequate, prioritizing higher priority data, and potentially duplicating data across both MCG and SCG to enhance redundancy and performance under variable radio conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If data transport is scheduled via secondary cell group (SCG) to utilize additional radio resources, then data throughput is improved, but reliability deteriorates when SCG performance falls below threshold under varying signal conditions
Solution Approach 1:
The system proactively monitors SCG performance metrics (RSRP, SINR, throughput) and triggers a handover to MCG before complete link failure occurs. By detecting performance degradation below predefined thresholds and initiating resource reallocation in advance, the system prevents data transport failures rather than reacting after they occur.
Solution Approach 2:
The patent implements dynamic resource allocation where the primary radio link (MCG or SCG) is flexibly switched based on real-time signal conditions. The system continuously evaluates performance metrics and adapts the data transport path, transitioning from static to dynamic resource management to maintain reliability under varying channel conditions.
2Reliability
If radio resources are reallocated from secondary cell group (SCG) to master cell group (MCG) to maintain reliability, then data transport reliability is improved, but data throughput may deteriorate due to reduced resource utilization
Solution Approach 1:
The system changes operational parameters (resource allocation ratios, active cell group selection) based on measured signal conditions. When SCG performance degrades, parameters are adjusted to shift data transport to MCG; when SCG recovers, parameters revert to utilize SCG resources again, optimizing the trade-off between reliability and throughput through parameter adaptation.
Solution Approach 2:
The system performs preliminary evaluation of MCG availability and capacity before committing to handover. By assessing whether MCG can absorb the additional data load and by preparing resource allocation in advance, the system minimizes throughput loss during the transition while ensuring reliability is maintained.
3Reliability
If data is duplicated across both master cell group (MCG) and secondary cell group (SCG) to enhance redundancy, then reliability is improved, but use of energy deteriorates due to increased transmission activity
Solution Approach 1:
The system applies data duplication selectively rather than continuously. Duplication is activated only when performance metrics indicate potential link failure (partial action applied when needed), and deactivated when SCG performance is adequate. This avoids the excessive energy consumption of continuous duplication while maintaining reliability during critical periods.
Solution Approach 2:
The redundancy level dynamically adjusts based on real-time channel conditions. The system transitions between single-path transmission (energy-efficient) and dual-path duplication (reliability-efficient) modes, optimizing the energy-reliability trade-off by adapting the transmission strategy to current signal quality and application requirements.
4Reliability
If latency sensitive application data is prioritized over other data traffic, then service quality for latency-sensitive applications is improved, but device complexity increases due to multiple performance thresholds and monitoring requirements
Solution Approach 1:
The system segments data traffic into different priority classes (latency-sensitive vs. non-latency-sensitive) and applies different handling rules to each segment. By separating traffic management for different application types, the system can enforce strict quality requirements for latency-sensitive data without unnecessarily complicating the handling of other traffic, reducing overall management complexity through structured segmentation.
Solution Approach 2:
The system implements feedback loops that continuously monitor performance metrics (RSRP, SINR, throughput) and automatically trigger resource reallocation or duplication actions when thresholds are breached. This closed-loop control automates complex decision-making, reducing the need for manual configuration and simplifying device operation while maintaining high service quality for latency-sensitive applications.
Data Source
AI summary
This application describes methods and apparatus to manage data transport across multiple radio links for 5G-capable wireless devices. Under certain criteria, including performance of at least one radio link, a mobility state of a 5G-capable wireless device, and data transport requirements for a latency sensitive application session, the 5G-capable wireless device sends buffer status report (BSR) requests for one or more both of the radio links to prioritize and transition uplink (UL) data between radio links before a measurement reporting threshold is met. In some embodiments, the 5G-capable wireless device proactively sends BSR requests for radio resources before the UL data is generated by the latency sensitive application session. In some embodiments, the 5G-capable wireless device duplicates UL data for the latency sensitive application session across multiple radio links.