Intelligent Carrier Aggregation for Dynamic Traffic Optimization
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Solution Overview
Problem
Current wireless communication systems face limitations in dynamically configuring uplink and downlink carrier aggregation based on application and traffic status, leading to suboptimal data rates due to static preferences, which fail to maximize bandwidth utilization for specific user equipment device applications.
Innovation Solution
Implementing an intelligent carrier aggregation mechanism that evaluates usage parameters, such as uplink and downlink traffic patterns and application resource utilization, to dynamically configure carrier aggregation, maximizing either uplink or downlink carrier aggregation depending on the device's application and traffic centricity, thereby optimizing bandwidth usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If static carrier aggregation configuration is used, then system complexity is reduced, but data rate is limited and cannot be optimized for specific applications
Solution Approach 1:
The patent implements dynamic carrier aggregation configuration that adapts to changing application and traffic conditions. The system transitions from static pre-configuration to real-time dynamic configuration based on application requirements and network conditions, allowing the carrier aggregation parameters to change dynamically to maximize data rates for different scenarios
Solution Approach 2:
The system changes carrier aggregation parameters (such as number of component carriers, frequency bands, and aggregation modes) based on evaluated application and traffic conditions. By adjusting these parameters dynamically according to actual needs, the system optimizes data rates without requiring complete system redesign
2Productivity
If uplink carrier aggregation is maximized, then uplink data rate increases, but downlink bandwidth utilization may be suboptimal
Solution Approach 1:
The patent applies different carrier aggregation configurations to different directions (uplink and downlink) based on their specific requirements. Instead of using a uniform configuration, the system evaluates and optimizes uplink and downlink separately, allowing each direction to have the optimal bandwidth allocation for its specific traffic patterns and application needs
Solution Approach 2:
The system dynamically adjusts the balance between uplink and downlink carrier aggregation based on real-time traffic conditions and application requirements. When uplink-intensive applications are detected, the system maximizes uplink aggregation; when downlink-intensive applications are detected, it maximizes downlink aggregation, providing adaptive optimization for both directions
3Productivity
If downlink carrier aggregation is maximized, then downlink data rate increases, but uplink bandwidth utilization may be suboptimal
Solution Approach 1:
The patent implements direction-specific optimization where downlink carrier aggregation is maximized when downlink-intensive applications are detected, while maintaining the capability to optimize uplink when needed. This local quality approach ensures each direction receives appropriate bandwidth allocation based on its specific requirements rather than applying a one-size-fits-all configuration
Solution Approach 2:
The system dynamically switches between maximizing downlink carrier aggregation and maximizing uplink carrier aggregation based on real-time evaluation of application and traffic conditions. This dynamic adaptation allows the system to prioritize downlink for content-heavy applications while maintaining flexibility to switch to uplink prioritization when needed
4Productivity
If carrier aggregation is configured without application awareness, then configuration simplicity is maintained, but bandwidth utilization is suboptimal
Solution Approach 1:
The patent implements feedback mechanisms where the system continuously evaluates application characteristics and traffic patterns, then uses this feedback information to adjust carrier aggregation configuration. This closed-loop approach enables application-aware optimization without requiring overly complex manual configuration, as the system automatically adapts based on observed conditions
Data Source
AI summary
Facilitating application and/or traffic status aware intelligent carrier aggregation in advanced networks is provided herein. Operations of a method can comprise analyzing a traffic usage parameter of a mobile device and, based on a first determination that the traffic usage parameter consumes more uplink resources than downlink resources, configuring, the mobile device with an uplink carrier aggregation based on a first maximization of the uplink carrier aggregation and, thereafter, configuring the mobile device with an allowable downlink carrier aggregation. Alternatively, based on a second determination that the traffic usage parameter consumes more downlink resources than uplink resources, configuring the mobile device with a downlink carrier aggregation based on a second maximization of the downlink carrier aggregation and, thereafter, configuring the mobile device with an allowable uplink carrier aggregation. The uplink carrier aggregation and the downlink carrier aggregation can be non-static carrier aggregations.