Decision-Directed Gain Control for Low-Frequency Hum Noise
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Solution Overview
Problem
Existing signal gain control systems fail to effectively mitigate amplitude modulation caused by low-frequency noise, such as 'hum', which interferes with communication signals, leading to incorrect symbol decisions and amplitude errors.
Innovation Solution
A system incorporating an automatic gain controller with a decision-directed amplitude error detector and loop filter, which utilizes symbol decision and error values to produce an amplitude error signal and adjust the gain of the signal, thereby correcting amplitude noise and phase noise within specific frequency ranges.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If adaptive equalization is used to mitigate multipath propagation and Doppler spreading, then signal quality is improved, but system complexity increases due to time-variant characteristics requiring continuous adaptation
Solution Approach 1:
The equalizer is segmented into multiple independent taps, each with its own weight that can be independently adjusted. This allows the complex time-variant equalization task to be divided into simpler, manageable components that can be adapted separately, reducing overall system complexity while maintaining signal quality.
Solution Approach 2:
The system employs feedback mechanisms where detected symbols are fed back to adjust the equalizer weights continuously. This feedback loop enables automatic adaptation to changing channel conditions without manual intervention, improving signal quality while automating the complex adaptation process.
2Measurement precision
If feedback of detected symbols is used for adaptive equalization, then equalization accuracy is improved, but processing time increases due to continuous adaptation requirements
Solution Approach 1:
The equalizer weights are pre-adapted using training sequences or pilot symbols before actual data transmission. This preliminary action establishes initial weight values that provide accurate equalization from the start, reducing the need for continuous time-consuming adjustments during data processing.
Solution Approach 2:
The feedback-based weight adjustment operates continuously in the background during signal processing, rather than requiring discrete, time-consuming recalibration steps. This continuous adaptation maintains equalization accuracy without introducing significant processing delays.
3Power
If AC power fluctuation is present in the system, then power delivery is improved, but amplitude modulation noise is introduced at 50-60 Hz that interferes with communication signals
Solution Approach 1:
The system extracts and separates the 50-60 Hz amplitude modulation noise component from the desired communication signal using frequency-selective filtering. By isolating and removing this specific frequency range, the harmful noise is eliminated while preserving the power delivery function and the integrity of the communication signal.
Solution Approach 2:
An intermediate filtering stage is introduced between the power supply and the communication signal processing. This intermediary component (band-pass or notch filter) allows the AC power fluctuation to exist for power delivery purposes while blocking or attenuating the specific 50-60 Hz amplitude modulation noise from entering the communication signal path.
Data Source
AI summary
An apparatus comprising a slicer configured to produce a symbol decision value and a symbol error value utilizing, at least in part, a slicer input signal; and an automatic gain controller configured to facilitate the automatic control of a gain applied to the slicer input signal by producing a gain control signal, the automatic gain controller comprising a decision-directed amplitude error detector configured to utilize, at least in part, the symbol decision value and the symbol error value to produce an amplitude error signal, and a loop filter configured to utilize the amplitude error signal to produce the gain control signal.