Dynamic Tuning Weighting for Antenna Matching Networks
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Solution Overview
Problem
Current communication devices face challenges in achieving optimal antenna matching for duplex operation and carrier aggregation, as existing solutions often compromise on transmit (Tx) and receive (Rx) performance, leading to suboptimal results due to asymmetric link conditions and limited real-time tuning capabilities.
Innovation Solution
A communication device with a dynamic tuning system that adjusts weighting between Tx and Rx matching based on real-time conditions, using a closed loop tuning algorithm to converge to optimal or compromise solutions, and dynamically changing the tuning configuration for carrier aggregation operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a fixed tuning configuration is used for duplex operation, then the device can maintain simple operation, but the matching performance compromises between transmit and receive operations
Solution Approach 1:
The patent implements dynamic weighting factors that adjust the balance between transmit and receive matching performance in real-time based on operational conditions. The system transitions from a fixed tuning configuration to a dynamic one where the weighting between Tx and Rx performance can be adjusted according to actual link conditions, application type, and radio measurements.
Solution Approach 2:
The system changes the parameter of weighting factors between transmit and receive matching. By varying these weighting parameters based on operational conditions (such as data throughput, link margin, and operational function), the system optimizes matching performance for different scenarios without requiring complex manual tuning.
2Reliability
If real-time tuning is implemented to optimize matching performance, then the matching performance improves, but the device complexity increases
Solution Approach 1:
The system incorporates feedback mechanisms that monitor operational conditions (data throughput, link margin, operational function) and use this information to adjust the weighting factors between transmit and receive matching. This closed-loop feedback allows the system to automatically optimize performance without requiring complex manual intervention or overly sophisticated tuning algorithms.
Solution Approach 2:
The tuning system performs self-optimization by automatically adjusting weighting factors based on monitored operational conditions. The system serves itself by using built-in sensors and processors to detect current operating state and autonomously modify matching parameters, reducing the need for external intervention or complex user-configurable options.
3Reliability
If asymmetric weighting is applied based on operational function, then the matching performance for specific operations improves, but the adaptability to changing conditions decreases
Solution Approach 1:
The system dynamically adjusts weighting factors based on real-time operational conditions such as data throughput, link margin, and current operational function. Rather than using fixed asymmetric weighting, the system can transition between different weighting configurations as conditions change, maintaining optimal performance across diverse scenarios including voice, data, and carrier aggregation operations.
Data Source
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AI summary
A system that incorporates teachings of the subject disclosure may include, for example, determining first and second tuning states based on selections from first and second groups of tuning states, respectively, detecting an operational function of the communication device, adjusting weighting between the first and second tuning states according to the operational function resulting in an adjusted weighting, and determining a tuning configuration for a matching network of the communication device according to interpolation that utilizes the first and second tuning states in conjunction with the adjusted weighting. Other embodiments are disclosed.