Service Group Based Dynamic Optimization of WWAN WLAN Aggregation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing systems for WWAN and WLAN aggregation lack dynamic optimization of flow split ratios and resource allocation across service groups, leading to inefficient use of wireless resources and suboptimal performance.
Innovation Solution
A system that groups user equipment into service groups, each with its own virtualized medium access control layer, allowing for dynamic optimization of flow split ratios and resource allocation between WWAN and WLAN interfaces, using virtual resource blocks and schedulers to optimize downlink communications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If static flow mapping and routing are used for WWAN-WLAN aggregation, then system complexity is reduced, but wireless resource utilization efficiency deteriorates
Solution Approach 1:
The patent implements dynamic flow mapping and routing that adapts to changing network conditions. The system continuously monitors channel quality indicators (CQI), signal-to-interference-plus-noise ratio (SINR), and load conditions, then dynamically adjusts flow split ratios and routing decisions. This transforms the static system into a dynamic one that optimizes resource utilization in real-time without requiring complex manual configuration.
Solution Approach 2:
The patent establishes feedback loops where the system monitors performance metrics (throughput, latency, channel quality) and uses this information to adjust flow mapping and routing decisions. The base station receives channel state information from user equipment and dynamically modifies resource allocation based on this feedback, enabling the system to adapt to varying network conditions and improve overall efficiency.
2Measurement precision
If separate optimization is performed for each service group, then optimization precision is improved, but computational complexity increases
Solution Approach 1:
The patent segments the network into multiple service groups, each with its own optimization parameters and characteristics. By dividing the overall optimization problem into smaller, service-group-specific subproblems, the system achieves precise optimization for each group while managing computational complexity through modular processing. Each service group can be optimized independently based on its specific requirements and conditions.
Solution Approach 2:
The patent implements partial optimization by focusing computational resources on optimizing only the necessary parameters for each service group rather than performing exhaustive optimization across all possible parameters. This selective approach achieves sufficient optimization precision while keeping computational complexity manageable through targeted optimization efforts.
3Productivity
If dynamic flow mapping and routing are implemented, then wireless resource utilization is improved, but system complexity increases
Solution Approach 1:
The patent implements a universal optimization framework that handles multiple service groups, flow types, and network conditions through a single integrated system. The base station and user equipment are equipped with multi-functional capabilities to perform dynamic flow mapping, routing optimization, and resource allocation across different scenarios, reducing the need for separate specialized systems and managing overall complexity.
Solution Approach 2:
The patent introduces an intermediary optimization module that mediates between the base station and user equipment, handling the complex dynamic flow mapping and routing decisions. This intermediary layer abstracts the complexity from the core network functions while enabling sophisticated resource utilization optimization, acting as a buffer that manages system complexity centrally.
4Productivity
If joint optimization of flow split ratios and resource allocation is performed, then network performance is improved, but control complexity increases
Solution Approach 1:
The patent merges the optimization of flow split ratios and resource allocation into a unified joint optimization process. Instead of separately optimizing these parameters, the system combines them into a single coordinated optimization framework that simultaneously determines both flow splitting decisions and resource allocation, achieving better network performance while managing control complexity through integration rather than multiplication of separate control mechanisms.
Data Source
AI summary
A service group based dynamic optimization of WWAN and WLAN aggregation in user equipment (UE) is described. The UE has a first radio access technology (RAT) interface associated with a Wireless Wide Area Network (WWAN) based interface that is served by a corresponding base station (BS), and a second RAT interface associated with a Wireless Local Area Network (WLAN) based interface that is served by an Access Point (AP), wherein, for downlink communications, the first and second RAT interfaces are aggregated. Each UE belongs to at least one service group, wherein the UE performs service group based dynamic optimization of WWAN and WLAN aggregation, with flow split ratios and resource allocation between RAT interfaces being jointly optimized for each service group and each RAT interface.