Radio Receiver State Variable Optimization
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Radio frequency communication devices are often designed to operate under worst-case conditions, which occur only a small percentage of the time, leading to suboptimal performance in varying RF environments and device-specific parameter fluctuations.
Innovation Solution
A method involving real-time measurement and iterative adjustment of state variables within a radio receiver to optimize performance, using statistical weighting and environment data to refine settings, which are then shared across devices in similar environments to enhance talk time, standby time, and quality of service.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If radio is designed to meet specifications in worst possible conditions, then reliability under extreme conditions is improved, but performance in typical conditions deteriorates
Solution Approach 1:
The patent implements dynamic adjustment of state variables based on measured performance and statistical weighting. Instead of static worst-case design, the system continuously adapts parameters like frequency offsets and timing advances to match actual operating conditions, transitioning from a fixed design to a dynamic optimization approach.
Solution Approach 2:
The system changes operational parameters in real-time by measuring performance metrics and iteratively adjusting state variables within prescribed ranges. Statistical weighting is applied to identify improved values that provide performance improvement, allowing the radio to optimize parameters for typical conditions while maintaining capability to handle worst-case scenarios.
2Productivity
If state variables are adjusted to optimize for specific conditions, then performance in those conditions improves, but adaptability to varying environments deteriorates
Solution Approach 1:
The patent implements a feedback mechanism where performance is measured, state variables are iteratively adjusted, and statistical weighting is applied to guide future adjustments. This closed-loop system enables the radio to adapt to varying environments by continuously learning from performance measurements and adjusting parameters accordingly, rather than being optimized for a single condition.
Solution Approach 2:
The system performs preliminary measurements of performance metrics before making adjustments to state variables. By measuring performance first and then iteratively changing parameters within prescribed ranges, the system prepares optimal settings in advance for different operating conditions, enabling faster convergence to optimal values when conditions change.
3Productivity
If iterative adjustment of state variables is performed in real-time, then performance optimization improves, but processing time and complexity increase
Solution Approach 1:
The patent applies partial action by adjusting state variables within prescribed ranges rather than exhaustively searching all possible values. Statistical weighting is used to identify improved values that provide performance improvement without requiring complete optimization cycles, allowing real-time adjustments with reduced processing time while maintaining effectiveness.
Data Source
Figure 1
Figure 2~5
Figure 3a~3c
AI summary
A method involving receiving a real time communication signal at a radio receiver involves measuring at least one performance value associated with the radio receiver with an installed set of state variables; at a processor forming a part of the radio receiver: iteratively changing at least one of the state variables within a prescribed range in order to identify an improved value of the state variable that provides an improvement to the at least one performance value; storing the improved value of the state variable; applying a statistical weighting to the improved value and storing the statistical weighting; and adjusting the prescribed range of the state variable based upon the statistical weighting to provide a revised prescribed range that is statistically likely to contain state variable that provides improvement in the at least one performance value. This abstract is not to be considered limiting.