RF Signal Dynamic Range Compression Through Reference Subtraction
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Solution Overview
Problem
Existing methods for suppressing radio frequency interference (RFI) in radio frequency (RF) signals often require increasing the number of bits per sample to accommodate high-power interference, leading to increased network bandwidth requirements and computational complexity, especially when such interference is not consistently present.
Innovation Solution
A method involving the use of a reference signal to subtract interference components from the received signal, followed by re-quantization with a lower number of bits, allowing for efficient compression of the signal dynamic range and reducing the required network bandwidth while maintaining signal reconstruction accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the number of bits per sample is increased to accommodate high-power interference, then the signal can represent the full dynamic range, but the network bandwidth requirements and computational complexity increase
Solution Approach 1:
The patent extracts the interference component from the received signal by using a reference signal that correlates with the interference. The subtracted signal (original signal minus reference signal) removes the high-power interference portion, allowing the remaining signal to be represented with fewer bits while maintaining the desired signal quality.
Solution Approach 2:
The patent changes the parameter of bit depth dynamically: full precision is used for the reference signal to accurately represent interference, while reduced precision is used for the subtracted signal since the interference has been removed. This parameter change allows maintaining signal quality while reducing overall bandwidth requirements.
2Measurement precision
If the number of bits per sample is increased to accommodate high-power interference, then the signal can represent the full dynamic range, but the required network bandwidth increases
Solution Approach 1:
The interference component is extracted using correlation with a reference signal. By subtracting this extracted interference from the original received signal, the dynamic range of the remaining signal is reduced, allowing transmission with fewer bits per sample and thus reducing network bandwidth consumption.
Solution Approach 2:
The signal is segmented into two parts: the reference signal (interference component) and the subtracted signal (desired signal plus noise). Each part is processed and transmitted with appropriate bit depth, optimizing the overall bandwidth usage while maintaining signal integrity.
3Reliability
If interference suppression is always applied, then interference mitigation is effective, but the hardware and software complexity increases
Solution Approach 1:
The interference suppression is applied dynamically rather than statically. The system calculates correlation between the received signal and reference signal in real-time, and only applies suppression when significant interference is detected. This dynamic approach maintains effectiveness while reducing unnecessary processing complexity.
Solution Approach 2:
The system uses the received signal itself to generate the reference signal through autocorrelation or by using known interference patterns. This self-service approach eliminates the need for external reference signal generation hardware, reducing system complexity while maintaining interference mitigation capability.
Data Source
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AI summary
In order to allow for compressing the signal dynamics of a radio frequency (RF) signal (16) that includes a desired signal (18) and an interference signal (20), the invention proposes to sample the RF signal (16) received by one or more antenna elements (14). One of the samples is used as a reference sample and subtracted at each sampling epoch (t0, t1, ...) from the received signal as it is output from each antenna element (14). The reference signal (30) and the subtracted signal are quantized such that the subtracted signal is quantized with a smaller number of quantization bits than the reference signal samples.