Non-Uniform Signal Sampling for Low-Power Band Detection
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Solution Overview
Problem
Existing methods for detecting signals in a frequency band require high sampling rates and large numbers of samples at high frequencies, leading to increased processing power and potential aliasing issues in receivers.
Innovation Solution
The use of non-uniform sampling techniques reduces the number of samples needed by varying sampling times based on the slope of the input signal or using pseudo random generators, allowing for efficient detection of signal presence in a frequency band without aliasing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If uniform sampling is used to detect signal presence in frequency band, then measurement precision is improved, but processing power requirements increase and aliasing occurs at high frequencies
Solution Approach 1:
The patent changes the sampling parameter from uniform to non-uniform intervals. By varying the sampling time intervals dynamically, the system achieves accurate signal detection in frequency bands while reducing the total number of samples needed, thereby lowering processing power requirements and avoiding aliasing at high frequencies.
Solution Approach 2:
The sampling rate is made dynamic rather than static. The system adjusts sampling intervals based on signal characteristics and frequency band requirements, allowing efficient detection with fewer samples at high frequencies while maintaining measurement precision through adaptive sampling density.
2Measurement precision
If large number of samples are taken at high frequencies to overcome aliasing, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The patent changes the sampling parameter from uniform to non-uniform intervals. By varying the sampling time intervals dynamically, the system achieves accurate signal detection in frequency bands while reducing the total number of samples needed, thereby lowering processing power requirements and avoiding aliasing at high frequencies.
3Power
If non-uniform sampling is used to reduce processing power, then power consumption is reduced, but measurement precision may deteriorate
Solution Approach 1:
The sampling rate is made dynamic rather than static. The system adjusts sampling intervals based on signal characteristics and frequency band requirements, allowing efficient detection with fewer samples at high frequencies while maintaining measurement precision through adaptive sampling density.
Solution Approach 2:
Different sampling densities are applied to different frequency bands or time periods. The system uses higher sampling density where signals are present or expected, and lower density where no signals are detected, optimizing both precision and power consumption locally rather than uniformly across all conditions.
Data Source
AI summary
A method and apparatus for detecting the presence of a signal in a frequency band using non-uniform sampling includes an analog to digital converter (ADC) (110) for sampling an analog input signal (105) to create discrete signal samples (115), an ADC exciter (120) for exciting the ADC to sample at non-uniform time periods, a digital filter (130) for converting the discrete signal samples into an energy versus frequency spectrum (300), and an energy comparator (140) coupled to an output of the digital filter. The energy comparator (140) detects the presence of any frequency bands exceeding an energy setpoint.