Frequency Sub-band Detection for Wireless Microphones
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Solution Overview
Problem
Current methods for detecting wireless microphone signals in cognitive radio systems are inefficient due to the lack of distinct characteristics in their signals, making it difficult to protect them from interference, especially in narrowband contexts where broadband solutions are not precise enough.
Innovation Solution
A process and device for detecting a frequency sub-band within a broader frequency band by performing frequential analysis, breaking down the signal into smaller sub-bands, determining a criterion based on energy and autocorrelation coefficients, and deciding on signal presence in each sub-band, allowing for more precise and faster detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If broadband detection solutions are used to detect wireless microphone signals, then the detection coverage is improved, but the detection precision deteriorates
Solution Approach 1:
The patent divides the broadband frequency range into multiple narrowband sub-bands. Each sub-band is detected separately using detection algorithms that operate independently on each frequency segment. This segmentation allows the system to maintain broad coverage while achieving high precision in each individual sub-band, resolving the contradiction between coverage area and measurement precision.
2Measurement precision
If narrowband detection is used for each TV channel, then the detection precision is improved, but the detection speed deteriorates
Solution Approach 1:
The patent merges multiple narrowband detection operations into a unified broadband detection framework. By processing multiple sub-bands simultaneously using parallel detection algorithms and combining the results, the system achieves detection speeds comparable to broadband methods while maintaining the precision of narrowband analysis. This merging resolves the contradiction between precision and productivity.
3Reliability
If multiple detection algorithms are combined to improve detection accuracy, then the detection reliability is improved, but the device complexity increases
Solution Approach 1:
The patent applies different detection algorithms to different frequency sub-bands based on their specific characteristics. Instead of using a single complex algorithm across the entire bandwidth or uniformly complex algorithms in each sub-band, the system selects appropriate detection methods for each local frequency region. This local quality approach improves overall detection reliability while keeping the complexity of each individual algorithm manageable.
Data Source
AI summary
The invention relates to a process for detection of a signal in a frequency sub-band of a frequency band of an acquired signal y(t), the process comprising:acquisition of the signal y(t) in a frequency band;frequential analysis of said acquired signal y(t) to obtain at least one frequential signal Y with NFFT frequential components;breakdown into M frequency sub-bands i of size N of the frequential signal Y, the size of each frequency sub-band being a function of the bandwidth of the signal to be detected;determination, in the frequential domain, for each frequency sub-band, of a criterion Ti, i=1, . . . , M as a function of the energy of the signal in the frequency sub-band i and of the coefficient two of the autocorrelation function of the signal in the frequency sub-band i;decision, as a function of the criterion Ti, to determine whether a signal is detected in the sub-band i.