Communications Toolbox

Using MLSE Equalizers

The mlseeq function uses the Viterbi algorithm to equalize a signal through a dispersive channel. The function receives a baseband linearly modulated input signal and outputs the maximum likelihood sequence estimate of the signal, using an estimate of the channel modeled as a finite input response (FIR) filter.

The function decodes the received signal using these steps:

1. Applies the FIR filter, corresponding to the channel estimate, to the symbols in the input signal.

2. Uses the Viterbi algorithm to compute the traceback paths and the state metric, which are the numbers assigned to the symbols at each step of the Viterbi algorithm. The metrics are based on Euclidean distance.

3. Outputs the maximum likelihood sequence estimate of the signal, as a sequence of complex numbers corresponding to the constellation points of the modulated signal.

An MLSE equalizer yields the best possible performance, in theory, but is computationally intensive. These topics describe how to use the MLSE equalizer capabilities in this toolbox:

• Equalizing a Vector Signal

• Equalizing in Continuous Operation Mode

• Using a Preamble or Postamble

For background material about MLSE equalizers, see the works listed in Selected Bibliography for Equalizers.

Equalizing Using a Loop

Equalizing a Vector Signal

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