||It has been suggested that this article be merged into Equalization. (Discuss) Proposed since January 2013.|
In digital communications, its purpose is to reduce intersymbol interference to allow recovery of the transmit symbols. It may be a simple linear filter or a complex algorithm. The following equalizer types are commonly used in digital communications:
- Linear Equalizer: processes the incoming signal with a linear filter
- Decision Feedback Equalizer: augments a linear equalizer by adding a filtered version of previous symbol estimates to the original filter output.
- Blind Equalizer: estimates the transmitted signal without knowledge of the channel statistics, using only knowledge of the transmitted signal's statistics.
- Adaptive Equalizer: is typically a linear equalizer or a DFE. It updates the equalizer parameters (such as the filter coefficients) as it is processes the data. Typically, it uses the MSE cost function; it assumes that it makes the correct symbol decisions, and uses its estimate of the symbols to compute e, which is defined above.
- Viterbi Equalizer: Finds the maximum likelihood (ML) optimal solution to the equalization problem. Its goal is to minimize the probability of making an error over the entire sequence.
- BCJR Equalizer: uses the BCJR algorithm (also called the Forward-backward algorithm) to find the maximum a posteriori (MAP) solution. Its goal is to minimize the probability that a given bit was incorrectly estimated.
- Turbo equalizer: applies turbo decoding while treating the channel as a convolutional code.
Below is a list of equalizers with applications in analogue communications:
- Interactive demonstration of various linear and non-linear equalizers
- Interactive demonstration of a Viterbi equalizer
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