Dynamic Signal Sampling Rate for Power-Aware DSP Processing
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Solution Overview
Problem
Signal processing systems face challenges in efficiently managing power consumption due to their processor-intensive nature, as the maximum bandwidth they support directly correlates with their power requirements, leading to excessive energy usage when handling signals with varying frequencies.
Innovation Solution
A dynamic data rate signal processing system that adjusts the processing frequency of a CPU or processor in real-time by determining the maximum frequency of an input signal and using a decimator/interpolator mechanism to set an optimal sampling rate, thereby ensuring adequate processing resources without unnecessary energy expenditure.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the system processes signals at maximum bandwidth capacity, then processing capability is improved, but power consumption increases
Solution Approach 1:
The patent implements dynamic adjustment of the sampling rate based on the actual frequency content of the input signal. The system continuously monitors signal characteristics and adapts the processing rate in real-time, transitioning from static maximum-bandwidth processing to dynamic rate adjustment. This allows the system to maintain adequate processing capability while reducing power consumption when full bandwidth is not required.
Solution Approach 2:
The system changes the sampling rate parameter according to the detected maximum frequency of the input signal. By adjusting this key parameter dynamically rather than operating at a fixed maximum rate, the system optimizes the balance between processing capability and power consumption, processing only what is necessary for the current signal conditions.
2Measurement precision
If the sampling rate is increased to capture higher frequencies, then signal accuracy is improved, but processing requirements increase
Solution Approach 1:
The system dynamically adjusts the sampling rate to match the actual signal frequency content rather than using a fixed high rate. This dynamic adaptation ensures sufficient signal accuracy for the current frequency range while reducing processing requirements compared to always operating at maximum sampling rates.
Solution Approach 2:
The system applies partial action by using only the sampling rate necessary for the current signal conditions. Instead of always applying excessive sampling rates to ensure accuracy, the system adjusts to provide just enough sampling precision for the actual frequency content, reducing unnecessary processing complexity.
3Speed
If the system maintains high processing speed continuously, then responsiveness is improved, but energy efficiency deteriorates
Solution Approach 1:
The system implements dynamic speed adjustment by continuously monitoring input signal characteristics and adapting the processing rate accordingly. This maintains high responsiveness when needed while improving energy efficiency during lower-frequency signal periods, eliminating the need for continuous high-speed processing.
Solution Approach 2:
The system employs periodic monitoring of signal frequency content and adjusts processing speed in response to these periodic assessments. This allows the system to maintain readiness and responsiveness while avoiding continuous high-energy consumption, achieving energy efficiency through rhythmic adaptation rather than constant high-speed operation.
Data Source
AI summary
As part of a signal processing event, the maximum frequency of an input signal can be determined with a processor. The maximum frequency can be compared to a value generated with a decimator/interpolator. Based on the comparison, the sampling rate for sampling the input signal with the processor can be set as part of the digital signal processing event. The sampling rate can be adjusted as the frequency of the input signal varies during the signal processing event.