Model-Based Optical Detection With Emitter-State Feedback Against ISI
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Solution Overview
Problem
Optical communication systems using semiconductor light sources face challenges with inter-symbol interference (ISI) due to the memory effect of electro-optical converters, leading to deteriorated signal-to-noise ratio (SNR) and limited bit rates, especially in short-range channels.
Innovation Solution
A model-based detection scheme that estimates the state of the electro-optical converter at the transmitter using a feedback model to predict and subtract inter-symbol interference, employing an infinite impulse response (IIR) operation to improve detection accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If linear equalizers are used to invert the channel characteristic and boost high-frequency signals, then bandwidth utilization is improved, but noise is amplified which deteriorates signal-to-noise ratio
Solution Approach 1:
The patent implements a decision feedback equalizer that uses feedback from detected symbols to compensate for inter-symbol interference. The equalizer uses a feedback filter to subtract the interference contribution from previous symbols from the current received signal, avoiding noise amplification while maintaining bandwidth utilization.
Solution Approach 2:
The patent extracts and removes the inter-symbol interference component from the received signal using the feedback mechanism. By identifying and subtracting the specific interference contribution from previous symbols, the system eliminates the harmful effect without amplifying the noise component.
2Measurement precision
If pre-distortion or post-equalization is applied to compensate for channel effects, then signal distortion is reduced, but signal-to-noise ratio is significantly degraded
Solution Approach 1:
The decision feedback equalizer uses feedback from symbol decisions to compensate for distortion. By using the detected symbol values to calculate and subtract the interference contribution, the system achieves distortion compensation without the noise amplification problems of pre-distortion and post-equalization methods.
Solution Approach 2:
The equalizer performs preliminary compensation for inter-symbol interference by calculating the expected interference from previous symbols and subtracting it before making the final symbol decision. This preliminary action removes distortion while avoiding noise amplification.
3Productivity
If higher bit rates are used to increase data throughput, then productivity is improved, but inter-symbol interference increases due to limited bandwidth
Solution Approach 1:
The decision feedback equalizer enables higher bit rates by continuously compensating for inter-symbol interference through feedback. The feedback mechanism tracks and removes the interference caused by previous symbols, allowing the system to operate at higher speeds without significant quality degradation.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The proposed method effectively suppresses ISI, enabling higher bit rates and improved SNR in optical communication systems, particularly over optical fibers, by accurately reconstructing digital symbol information.
Implementation Method 1
a photodetector for receiving the optical signal
Data Source
AI summary
This invention relates to a receiver configured to exploit physical phenomena of a memory in an electro-optical converter of an emitter (e.g., LED) at a transmitting end. The memory can be described as a state that is a function of an input signal of the emitter, while the emitted light is a function of the state. An incoming symbol bit sequence and corresponding state(s) of the electro-optical converter are estimated (e.g., in terms of time varying carrier concentration or charge in a quantum well) to derive a decision for a state of a received symbol. This estimation can be done for multiple levels of incoming data (e.g., at least for hypothesized binary values).