Negative-Covariance Filter Receiver for Closed-Eye Signal Detection
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Solution Overview
Problem
Existing receivers struggle to quickly and accurately restore transmission signals lost due to inter-symbol interference (ISI) and noise, especially when the eye diagram is closed, making it difficult to detect data accurately.
Innovation Solution
A receiver is equipped with a pre-processing block, an equalization block, and a threshold generation block that generates pre-processing and equalization signals, along with error and data threshold values, using a negative covariance relation to quickly and accurately calculate threshold values, thereby improving signal restoration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional equalization methods are used to restore transmission signals, then signal restoration is achieved, but the process is slow and inaccurate especially when the eye diagram is closed
Solution Approach 1:
The patent applies preliminary action by pre-calculating and storing threshold values in a lookup table before actual signal restoration is needed. The threshold generation block generates error threshold values and data threshold values in advance based on filter signals, so when signal restoration is required, the pre-computed thresholds can be immediately retrieved and applied, eliminating the time-consuming calculation process during critical signal restoration operations.
Solution Approach 2:
The patent uses copying by creating a filter signal that is a processed version of the equalization signal, specifically designed to have negative covariance between adjacent symbols. This filter signal serves as a template or copy that captures the essential statistical properties needed for threshold calculation, allowing accurate threshold generation without requiring complex real-time analysis of the original distorted signal.
2Reliability
If complex equalization processing is applied to handle severe ISI conditions, then signal restoration accuracy improves, but processing complexity and time increase
Solution Approach 1:
The patent applies parameter changes by transforming the equalization signal into a filter signal with specific statistical properties (negative covariance between adjacent symbols). This parameter transformation simplifies the subsequent threshold calculation process. By changing the signal representation to one with favorable statistical characteristics, the system achieves reliable data detection without requiring complex processing algorithms.
Solution Approach 2:
The threshold generation block performs self-service by autonomously generating error threshold values and data threshold values from the filter signal without requiring external intervention or complex adaptive algorithms. The system uses the inherent statistical properties of the filter signal (negative covariance) to automatically determine appropriate thresholds, making the equalization process more straightforward and less complex.
3Productivity
If traditional threshold calculation methods are used, then processing is straightforward, but accurate threshold values cannot be generated quickly under severe ISI conditions
Solution Approach 1:
The patent applies preliminary action by pre-generating and storing threshold values in a lookup table structure. The threshold generation block computes error threshold values and data threshold values in advance based on the statistical properties of the filter signal, organizing them for rapid retrieval. This pre-computation approach enables both high productivity (fast threshold generation) and high precision (accurate thresholds) by avoiding real-time calculations during critical detection phases.
Solution Approach 2:
The patent uses an intermediary approach by introducing the filter signal as a intermediate representation between the equalization signal and the threshold values. The filter signal, with its negative covariance property, serves as a mediator that simplifies the relationship between the distorted input signal and the required threshold parameters, enabling both fast and accurate threshold generation through this intermediate statistical representation.
Data Source
AI summary
Disclosed is a receiver including a pre-processing block that pre-processes a received signal transmitted from an external transmitter and generates a pre-processing signal, an equalization block that generates an equalization signal based on the pre-processing signal and error threshold values, and a threshold generation block that generates the error threshold values and data threshold values. The threshold generation block generates a delay signal obtained by delaying the equalization signal by a unit time interval, generates a filter signal based on subtracting the delay signal from the equalization signal, and generates the error threshold values and the data threshold values based on the filter signal.