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mmseweights

Linear equalizer MMSE tap weights

Description

example

weights = mmseweights(eq,chTaps,EbN0) calculated minimum mean squared error (MMSE) solution for the linear equalizer, eq System object™ given the channel delay taps, chTaps, and signal to noise ratio, EbN0.

Examples

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Calculate the minimum mean squared error (MMSE) solution and use the weights for the linear equalizer taps weights.

Initialize simulation variables.

M = 4; % QPSK
numSymbols = 10000;
numTrainingSymbols = 1000;
chtaps = [1 0.5*exp(1i*pi/6) 0.1*exp(-1i*pi/8)];
EbN0 = 20;

Generate QPSK modulated symbols. Apply delayed multipath channel filtering and AWGN impairments to the symbols.

data = randi([0 M-1], numSymbols, 1);
tx = pskmod(data, M, pi/4);
rx = awgn(filter(chtaps,1,tx),25,'measured');

Create a linear equalizer System object configured to use CMA algorithm and input the taps weights. Calculate the MMSE weights. Set the initial tap weights to the calculated MMSE weights. Equalize the impaired symbols.

eq = comm.LinearEqualizer('Algorithm','CMA','AdaptWeights',false,'InitialWeightsSource','Property')
eq = 
  comm.LinearEqualizer with properties:

                Algorithm: 'CMA'
                  NumTaps: 5
                 StepSize: 0.0100
            Constellation: [1x4 double]
    InputSamplesPerSymbol: 1
       AdaptWeightsSource: 'Property'
             AdaptWeights: false
     InitialWeightsSource: 'Property'
           InitialWeights: [5x1 double]
       WeightUpdatePeriod: 1

wgts = mmseweights(eq,chtaps,EbN0)
wgts = 5×1 complex

   0.0005 - 0.0068i
   0.0103 + 0.0117i
   0.9694 - 0.0019i
  -0.3987 + 0.2186i
   0.0389 - 0.1756i

eq.InitialWeights = wgts;

[y,err,weights] = eq(rx);

Plot constellation of impaired and equalized symbols.

constell = comm.ConstellationDiagram('NumInputPorts',2);
constell(rx,y)

Figure Constellation Diagram contains an axes and other objects of type uiflowcontainer, uimenu, uitoolbar. The axes contains 4 objects of type line. These objects represent Channel 1, Channel 2.

Plot the equalizer error signal and compute the error vector magnitude of the equalized symbols.

plot(abs(err))
grid on; xlabel('Symbols'); ylabel('|e|')

Figure contains an axes. The axes contains an object of type line.

errevm = comm.EVM;
evm = errevm(tx,y)
evm = 140.6177

Plot equalizer tap weights.

subplot(3,1,1); stem(real(weights)); ylabel('real(weights)'); xlabel('Tap'); grid on; axis([1 8 -0.5 1])
line([eq.NumTaps+0.5 eq.NumTaps+0.5], [-0.5 1], 'Color', 'r', 'LineWidth', 1)
title('Equalizer Tap Weights')
subplot(3,1,2); stem(imag(weights)); ylabel('imag(weights)'); xlabel('Tap'); grid on; axis([1 8 -0.5 1])
line([eq.NumTaps+0.5 eq.NumTaps+0.5], [-0.5 1], 'Color', 'r', 'LineWidth', 1)
subplot(3,1,3); stem(abs(weights)); ylabel('abs(weights)'); xlabel('Tap'); grid on; axis([1 8 -0.5 1])
line([eq.NumTaps+0.5 eq.NumTaps+0.5], [-0.5 1], 'Color', 'r', 'LineWidth', 1)

Figure contains 3 axes. Axes 1 with title Equalizer Tap Weights contains 2 objects of type stem, line. Axes 2 contains 2 objects of type stem, line. Axes 3 contains 2 objects of type stem, line.

Input Arguments

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Equalizer object, specified as a comm.LinearEqualizer System object.

Channel delay taps, specified as a vector.

Data Types: double
Complex Number Support: Yes

Signal to noise ratio of the channel, specified as a scalar.

Data Types: double

Output Arguments

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Weights for linear equalizer, returned as a vector.

See Also

Objects

Introduced in R2019a