Fractional Radio Mapping for Wireless Device Throughput
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Solution Overview
Problem
Wireless communication devices face challenges in efficiently managing multiple radios to support active applications, leading to suboptimal performance, increased power consumption, and network traffic impact due to the limitations of existing full system selection methods.
Innovation Solution
The implementation of fractional system selection, where the wireless device maps different portions or fractions of an application to multiple radios based on application requirements, radio capabilities, interference, and channel conditions, allowing for dynamic allocation of resources and improved performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If full system selection is used to support multiple applications, then device complexity increases, but application performance and throughput are limited
Solution Approach 1:
The patent segments applications into multiple flows and maps different flows to different radios, enabling parallel processing and increased throughput. This segmentation allows the system to achieve high productivity without requiring all applications to share a single radio, thus resolving the contradiction between throughput and complexity.
Solution Approach 2:
The system dynamically adjusts the mapping between applications, flows, and radios based on real-time conditions such as channel quality and radio availability. This dynamic adaptation enables the system to optimize throughput while managing complexity through flexible, condition-based resource allocation rather than static rigid mappings.
2Productivity
If multiple radios are activated to improve application performance, then throughput increases, but power consumption increases
Solution Approach 1:
By segmenting applications into flows and distributing them across multiple radios, the system can activate only the necessary number of radios for current workload requirements. This segmentation enables fine-grained power management where radios can be selectively activated/deactivated based on actual usage patterns, reducing overall power consumption while maintaining high throughput when needed.
Solution Approach 2:
The system changes operational parameters of radios including activation status, transmission power levels, and mapping configurations based on real-time conditions. This parameter adjustment allows the system to optimize the balance between throughput and power consumption by activating additional radios only when and where needed, rather than maintaining all radios in high-power states continuously.
3Productivity
If fractional system selection is implemented to improve performance, then throughput increases, but device complexity increases
Solution Approach 1:
The patent introduces a flow manager as an intermediary component that handles the complexity of mapping applications to radios. This mediator abstracts the complex fractional mapping logic from the application layer, managing the relationships between flows, radios, and channel conditions. The flow manager centralizes the complexity management, allowing the rest of the system to benefit from high throughput without directly managing the intricate mapping relationships.
4Productivity
If dynamic radio mapping is performed to optimize performance, then application performance improves, but processing time and overhead increase
Solution Approach 1:
The system performs preliminary actions by pre-establishing flow-to-radio mappings based on predicted conditions and application requirements. This preliminary configuration reduces the time needed for real-time mapping decisions by having ready-to-use mapping templates that can be quickly activated when conditions change, rather than performing complex optimization calculations at the moment of decision.
Solution Approach 2:
The system implements feedback mechanisms that continuously monitor radio performance and channel conditions, adjusting mappings based on actual measured outcomes. This feedback enables the system to learn from past performance and make faster, more informed mapping decisions in the future, reducing processing time while maintaining optimal application performance through adaptive refinement of mapping strategies.
Data Source
AI summary
Techniques for performing fractional system selection by a wireless device are described. The wireless device may have at least one application that is active and a plurality of radios that are available for use. The wireless device may perform fractional system selection and map different portions of an application to different radios. In one design, the wireless device may determine a mapping of different fractions of the application to different radios based on the requirements of the application, capabilities of the radios, interference between the radios, etc. The wireless device may map a first fraction of the application to a first radio and may map a second fraction of the application to a second radio. The wireless device may exchange (e.g., send or receive) data for the first fraction of the application via the first radio and may exchange data for the second fraction of the application via the second radio.