PAM-N Receiver Equalizer Adaptive Training
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Solution Overview
Problem
Conventional PAM-N receivers lack the ability to adaptively select high-frequency and low-frequency amplification gains and tap coefficients based on the state of the received signal and transmission line characteristics, leading to inadequate equalization.
Innovation Solution
A method for training a PAM-N receiver equalizer system using specific training data patterns to adjust the high-frequency and low-frequency amplification gains and tap coefficients, ensuring proper equalization by comparing output signal levels with predetermined limits and thresholds.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If multi-level PAM (PAM-4, PAM-8, PAM-N) is used to transmit digital data at high speed, then data transmission rate is improved, but susceptibility to attenuation and noise increases
Solution Approach 1:
The patent implements an equalizer system with feedback mechanisms that continuously monitor the received signal quality and adjust equalization parameters accordingly. The receiver uses the equalized signal to generate feedback that optimizes the equalizer coefficients, thereby compensating for channel attenuation and noise effects while maintaining high-speed PAM-N transmission
Solution Approach 2:
The patent dynamically changes equalization parameters (such as equalizer coefficients and amplification gains) based on the received signal characteristics. By adjusting these parameters in response to varying channel conditions, the system maintains optimal performance for high-speed PAM-N transmission despite attenuation and noise
2Device complexity
If conventional PAM-N receiver equalizer is used without adaptive training, then device complexity is reduced, but equalization performance deteriorates
Solution Approach 1:
The patent implements a training sequence mechanism where the receiver预先 (in advance) receives known training patterns before actual data transmission. This preliminary action allows the equalizer to pre-adjust its coefficients and amplification gains based on the training data, ensuring accurate equalization when real data arrives without adding complex adaptive algorithms during data reception
Solution Approach 2:
The equalizer system performs self-calibration using the training sequences. The receiver automatically adjusts its equalization parameters based on the known training patterns without external intervention or complex manual configuration, achieving high equalization accuracy while maintaining relatively simple device architecture
3Device complexity
If fixed amplification gains are used in CTLE and DFE, then device complexity is reduced, but adaptability to different signal conditions deteriorates
Solution Approach 1:
The patent transforms the static amplification gains into dynamic parameters that can be adjusted based on training data. The CTLE high-frequency gain and low-frequency gain, as well as DFE tap coefficients, are updated during the training phase to match the actual channel conditions, enabling adaptability without requiring complex real-time control mechanisms during data reception
Data Source
AI summary
A method of adaptively training an equalizer system of a PAM-N receiver is disclosed. The method of training an equalizer system according to the present invention employs a training pattern including a first training data pattern and second training data pattern to tune the continuous-time linear equalizer, decision feedback equalizer and sampler constituting the equalizer system before use in actual communication enabling long-distance, high-speed communication.