(To be removed) Equalize using constant modulus algorithm
CMA Equalizer will be removed in a future release. Use Linear Equalizer instead.
The CMA Equalizer block uses a linear equalizer and the constant modulus algorithm
(CMA) to equalize a linearly modulated baseband signal through a dispersive channel.
During the simulation, the block uses the CMA to update the weights, once per symbol. If
the Number of samples per symbol parameter is
then the block implements a symbol-spaced equalizer; otherwise, the block implements a
fractionally spaced equalizer.
When using this block, you should initialize the equalizer weights with a nonzero vector. Typically, CMA is used with differential modulation; otherwise, the initial weights are very important. A typical vector of initial weights has a 1 corresponding to the center tap and zeros elsewhere.
Input port accepts a scalar-valued or column vector input
Desired port receives a training sequence with a
length that is less than or equal to the number of symbols in the
You can configure the block to have one or more of the extra ports listed in the table below.
|Port||Meaning||How to Enable|
|y(R -|y|2), where y is the equalized signal and R is a constant related to the signal constellation||Select Output error.|
|A vector listing the weights after the block has processed either the current input frame or sample.||Select Output weights.|
Referring to the schematics in Adaptive Equalizers, define w as the vector of all weights wi and define u as the vector of all inputs ui. Based on the current set of weights, w, this adaptive algorithm creates the new set of weights given by
LeakageFactor) w + (
where the * operator denotes the complex conjugate.
The delay between the transmitter's modulator output and the CMA equalizer output is typically unknown (unlike the delay for other adaptive equalizers in this product). If you need to determine the delay, you can use the Find Delay block.
The number of taps in the filter of the equalizer.
The number of input samples for each symbol.
When you set this parameter to 1, the filter weights are updated once for each symbol, for a symbol spaced (i.e. T-spaced) equalizer. When you set this parameter to a value greater than one, the weights are updated once every Nth sample, for a fractionally spaced (i.e. T/N-spaced) equalizer.
A vector of complex numbers that specifies the constellation for the modulation.
The step size of the CMA.
The leakage factor of the CMA, a number between 0 and 1. A value of 1 corresponds to a conventional weight update algorithm, and a value of 0 corresponds to a memoryless update algorithm.
A vector that lists the initial weights for the taps.
If you check this box, the block outputs the error signal described in the table above.
If you check this box, the block outputs the current weights.
 Haykin, Simon, Adaptive Filter Theory, Third Ed., Upper Saddle River, N.J., Prentice-Hall, 1996.
 Johnson, Richard C. Jr., Philip Schniter, Thomas. J. Endres, et al., "Blind Equalization Using the Constant Modulus Criterion: A Review," Proceedings of the IEEE, vol. 86, pp. 1927-1950, October 1998.
Warns starting in R2020a