Dominant Signal Detection by Iterative Frequency Range Narrowing
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Solution Overview
Problem
Existing methods for identifying and mitigating dominant or blocker signals in communication systems are inefficient, as they often require extensive scanning and computational resources, especially when dealing with weak desired signals and strong interferer signals.
Innovation Solution
A method and apparatus that iteratively analyze an input signal by selecting a test range of frequencies, using filtering and Fourier transform techniques to identify dominant or significant frequency components, and recursively narrow the search range to achieve sufficient frequency resolution, employing parametric engines to estimate and refine the frequency of these components.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If extensive scanning is performed to identify dominant signals, then frequency detection capability is improved, but computational resources and time consumption increase
Solution Approach 1:
The frequency search range is divided into multiple frequency bins or sub-ranges. The algorithm performs iterative scanning where each iteration focuses on a specific bin, identifying dominant signals incrementally. This segmentation allows the system to achieve comprehensive frequency detection without requiring a single exhaustive scan, thereby reducing computational burden while maintaining detection capability.
Solution Approach 2:
The algorithm performs preliminary identification of dominant signals in broader frequency ranges before conducting more precise localized analysis. By first identifying candidate frequency regions and then focusing computational resources on those specific regions in subsequent iterations, the system achieves accurate frequency detection with reduced overall computational requirements.
2Measurement precision
If the search range is reduced to improve frequency resolution, then measurement precision is improved, but the risk of missing dominant signals increases
Solution Approach 1:
The algorithm dynamically adjusts the search range and frequency bin width across multiple iterations. In early iterations, broader frequency bins are used to ensure comprehensive coverage and identify candidate dominant signals. As iterations progress, the search range is refined and bins are narrowed to improve frequency resolution for identified signals, while the iterative nature ensures no signals are missed.
Solution Approach 2:
The algorithm uses feedback from each iteration to guide subsequent iterations. Dominant signals identified in one iteration inform the configuration of frequency bins and search ranges in the next iteration. This feedback mechanism ensures that the refined search process maintains reliability by focusing on regions where dominant signals have been detected, while adapting to the actual signal distribution in the input.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach allows for efficient identification of dominant signals with improved frequency resolution, reducing computational burden and enabling effective mitigation of interference by isolating and canceling blocker signals, thereby enhancing signal reception in communication systems.
Implementation Method 1
Selecting the test range may be achieved by filtering the input signal to attenuate frequencies outside of the test range
Implementation Method 2
The analysis engine may comprise a Fourier transform engine
Data Source
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Figure 3a~3c
AI summary
A single complex calculation for locating a dominant frequency, such as an interfering signal in a frequency range, is replaced by several much easier ones. A signal is analyzed over a first frequency range to locate at least one comparatively significant frequency component therein. This can involve analyzing, using electronic hardware, a test range of frequencies to identify a potentially significant component within the test range; and determining, using electronic hardware, if a condition for finishing the analysis has been met. If the condition has not been met, the test range is modified as a result of the analysis and the operations of analyzing and determining are repeated.