Estimating Channel Distortion via Adaptive Equalizer Coefficients
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional communications systems face challenges in estimating channel fidelity, especially for short bursts, as existing methods for channel equalization are not effective and require complex receivers or pre-equalization, which may not be practical due to cost, power consumption, and hardware limitations.
Innovation Solution
A method for estimating channel distortion using adaptive filter coefficients, where a communications channel is tested with training transmissions to determine equalization coefficients, allowing for reliable estimation of channel fidelity without equalization, and implementing pre-equalization if supported, using either time domain or frequency domain approaches to calculate channel linear distortion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional equalization techniques are used for short bursts, then channel fidelity can be improved, but the equalization cannot be triggered or retained due to burst duration being too short
Solution Approach 1:
The patent applies preliminary action by performing equalization during a longer training burst before the actual short data burst transmission. The equalizer coefficients are trained and established during the training phase, so that when the short burst occurs, the equalization is already in place and can immediately improve channel fidelity without requiring the short burst itself to be long enough to trigger equalization.
2Reliability
If pre-equalization is implemented to benefit short packets, then channel fidelity improves, but hardware complexity and cost increase due to requiring pre-equalization capability
Solution Approach 1:
The patent makes the receiver universal by designing it to handle both equalized and unequalized channels. The receiver can adaptively determine whether equalization is available and adjust its processing accordingly. This allows the system to benefit from pre-equalization when available while maintaining compatibility with legacy equipment that lacks pre-equalization capability, avoiding the need for all hardware to be complex.
Solution Approach 2:
The patent changes the parameter of equalization availability by providing a mechanism where the receiver can detect whether pre-equalization has been applied and adjust its operation accordingly. This allows the system to optimize performance when pre-equalization is present while degrading gracefully when it is absent, without requiring hardware complexity in all cases.
3Ease of manufacture
If traditional distortion estimation techniques are used, then implementation is possible, but the estimations are not particularly reliable
Solution Approach 1:
The patent applies feedback by using the equalizer coefficients themselves as a basis for estimating distortion. The equalizer, having already adapted to the channel conditions, provides information about the channel characteristics through its coefficients. This feedback mechanism allows for more reliable distortion estimation because the coefficients reflect the actual channel state that the equalizer has learned, rather than relying on separate estimation processes.
4Measurement precision
If more complex receivers are designed to improve channel fidelity estimation, then measurement accuracy improves, but cost, speed, and power consumption worsen
Solution Approach 1:
The patent applies self-service by having the equalizer perform dual functions: equalization and distortion estimation. The equalizer coefficients, which are necessarily computed during equalization, are reused to estimate channel distortion. This eliminates the need for separate complex estimation hardware, as the equalizer itself provides the estimation capability through its existing computational resources and coefficient data.
Data Source
AI summary
Provided is a method and system for estimating distortion in a communications channel including an adaptive equalizer. The method includes determining one or more adaptive filter coefficients associated with a signal passed through the equalizer. The method also includes estimating un-equalized channel distortion based upon the determined adaptive filter coefficients.