Non-Uniform ADC Sampling for Low-Power Signal Band Detection
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Solution Overview
Problem
Existing methods for detecting signals in frequency bands require high sampling rates at high frequencies, leading to increased processing and power consumption, which can stress receivers and result in aliasing issues.
Innovation Solution
The technique involves non-uniform sampling of analog signals to reduce the number of samples required, using a combination of slope detectors and pseudo random generators to determine sampling times, allowing for a slower average sampling rate and fewer samples while avoiding aliasing and maintaining effective signal detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If uniform sampling is used at high frequencies, then signal detection accuracy is improved, but processing power consumption increases and aliasing occurs
Solution Approach 1:
The patent applies dynamic sampling by adjusting the sampling rate according to the signal characteristics. The system uses a variable sampling rate that adapts to the detected signal frequency and amplitude, allowing higher sampling rates only when necessary for accurate detection while using lower rates during other periods, thus resolving the contradiction between detection accuracy and power consumption
Solution Approach 2:
The patent changes the sampling parameter from a fixed uniform rate to a variable rate based on signal conditions. By monitoring signal energy and frequency content, the system dynamically modifies the sampling interval, using shorter intervals when signals are detected and longer intervals when the spectrum is clear, thereby reducing overall processing power while maintaining detection accuracy
2Measurement precision
If uniform sampling is used at high frequencies, then signal detection accuracy is improved, but device complexity increases
Solution Approach 1:
The patent introduces dynamic control mechanisms that adjust sampling based on real-time signal conditions. The system includes signal energy detectors and frequency estimators that dynamically control the sampling rate, making the receiver adaptable to different spectral conditions rather than requiring continuously high sampling rates, thus reducing device complexity while maintaining detection capability
Solution Approach 2:
The patent segments the frequency spectrum into different regions and applies different sampling strategies to each segment. By dividing the broad frequency range into manageable segments and selectively sampling only those containing signals, the system reduces the overall sampling burden and simplifies the receiver architecture while maintaining comprehensive signal detection coverage
3Reliability
If uniform sampling is used, then complete signal coverage is achieved, but sampling rate must be high to avoid aliasing
Solution Approach 1:
The patent employs periodic scanning of the frequency spectrum where the system systematically moves through different frequency segments over time. Instead of continuously sampling all frequencies at high rates, the receiver periodically visits different frequency regions, detecting signals when present and reducing sampling rate when regions are clear, thus maintaining reliable detection while lowering the required sampling rate
Solution Approach 2:
The system dynamically adjusts the sampling rate based on the presence and characteristics of detected signals. When signals are detected in a frequency segment, the sampling rate increases to capture them accurately; when segments are clear, the sampling rate decreases, eliminating the need for continuously high sampling rates while maintaining detection reliability
Data Source
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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.