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serdes.FFE

Models a feed-forward equalizer

Description

The serdes.FFE System object™ applies a feed-forward equalizer (FFE) as a symbol-spaced finite-impulse response (FIR) filter. Apply the equalizer to a sample-by-sample input signal or an impulse response vector input signal to reduce distortions due to channel loss impairments.

To equalize the baseband signal:

  1. Create the serdes.FFE object and set its properties.

  2. Call the object with arguments, as if it were a function.

To learn more about how System objects work, see What Are System Objects?.

Creation

Description

ffe = serdes.FFE returns an FFE object that modifies an input waveform according to the finite impulse response (FIR) transfer function defined in the object.

ffe = serdes.FFE(Name,Value) sets properties using one or more name-value pairs. Enclose each property name in quotes. Unspecified properties have default values.

Example: ffe = serdes.FFE('Mode',1) returns an FFE object that applies specified tap weights to the input waveform.

Properties

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Unless otherwise indicated, properties are nontunable, which means you cannot change their values after calling the object. Objects lock when you call them, and the release function unlocks them.

If a property is tunable, you can change its value at any time.

For more information on changing property values, see System Design in MATLAB Using System Objects.

Main

FFE operating mode, specified as 0 or 1. Mode determines whether FFE is bypassed or not.

Mode ValueFFE ModeFFE Operation
0Offserdes.FFE is bypassed and the input waveform remains unchanged.
1Fixedserdes.FFE applies input FFE tap weights, specified in TapWeights, to input waveform.

Data Types: double

FFE tap weights, specified as a row vector in V. The length of the vector specifies the number of taps. Each vector element's value specifies the strength of the tap at that position. The tap with the largest magnitude is the main tap and therefore defines the number of pre- and post-cursor taps.

Data Types: double

Normalize tap weight vectors, specified as true or false. When set to true, the object scales the TapWeights vector elements so that the sum of their absolute values is 1.

Data Types: logical

Advanced

Time of a single symbol duration, specified as a real scalar in s.

Data Types: double

Uniform time step of the waveform, specified as a real scalar in s.

Data Types: double

Input waveform type:

  • 'Sample' — A sample-by-sample input signal

  • 'Impulse' — An impulse response input signal

Data Types: char

Usage

Description

y = ffe(x)

Input Arguments

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Input baseband signal. If the WaveType is set to 'Sample', the input signal is a sample-by-sample signal specified as a scalar. If the WaveType is set to 'Impulse', the input signal must be an impulse response vector signal.

Output Arguments

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Filtered channel output. If the input signal is a sample-by-sample signal specified as a scalar, the output is also scalar. If the input signal is an impulse response vector signal, the output is also a vector.

Object Functions

To use an object function, specify the System object as the first input argument. For example, to release system resources of a System object named obj, use this syntax:

release(obj)

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stepRun System object algorithm
releaseRelease resources and allow changes to System object property values and input characteristics
resetReset internal states of System object

Examples

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This example shows how to process impulse response of a channel using serdes.FFE System object™.

Use a symbol time of 100 ps and 16 samples per symbol. The channel has 16 dB loss.

SymbolTime = 100e-12;                  
SamplesPerSymbol = 16;
dbloss = 16;                                                  

Calculate the sample interval.

dt = SymbolTime/SamplesPerSymbol;

Create the FFE object with fixed mode of operation.

TapWeights = [0 0.7 -0.2 -0.10];
FFEMode = 1;   
FFE1 = serdes.FFE('SymbolTime',SymbolTime,'SampleInterval',dt,...
      'Mode',FFEMode,'WaveType','Impulse',...
      'TapWeights',TapWeights);

Create the channel impulse response.

channel = serdes.ChannelLoss('Loss',dbloss,'dt',dt,...
      'TargetFrequency',1/SymbolTime/2);
impulseIn = channel.impulse;

Process the impulse response with FFE.

impulseOut = FFE1(impulseIn);

Convert the impulse responses to pulse, waveform and eye diagram data for visualization in later steps. Initialize the pseudorandom binary sequence (PRBS).

ord = 6;
dataPattern = prbs(ord,2^ord-1)-0.5;

pulseIn = impulse2pulse(impulseIn,SamplesPerSymbol,dt);
waveIn = pulse2wave(pulseIn,dataPattern,SamplesPerSymbol);
eyeIn = reshape(waveIn,SamplesPerSymbol,[]);
 
pulseOut = impulse2pulse(impulseOut,SamplesPerSymbol,dt);
waveOut = pulse2wave(pulseOut,dataPattern,SamplesPerSymbol);
eyeOut = reshape(waveOut,SamplesPerSymbol,[]);

Create the time vectors.

t = dt*(0:length(pulseOut)-1)/SymbolTime;
teye = t(1:SamplesPerSymbol);
t2 = dt*(0:length(waveOut)-1)/SymbolTime;

Plot the pulse response comparison, waveform comparison, and input and output eye diagrams.

figure
plot(t,pulseIn,t,pulseOut)
legend('Input','Output')
title('Pulse Response Comparison')
xlabel('SymbolTimes'),ylabel('Voltage')
grid on
axis([47 60 -0.1 0.4])

figure
plot(t2,waveIn,t2,waveOut)
legend('Input','Output')
title('Waveform Comparison')
xlabel('SymbolTimes')
ylabel('Voltage')
grid on 

figure
subplot(211),plot(teye,eyeIn,'b')
ax = axis;
xlabel('SymbolTimes')
ylabel('Voltage')
grid on
title('Input Eye Diagram')
subplot(212),plot(teye,eyeOut,'b')
axis(ax);
xlabel('SymbolTimes')
ylabel('Voltage')
grid on
title('Output Eye Diagram')

This example shows how to process impulse response of a channel one sample at a time using serdes.FFE System object™.

Use a symbol time of 100 ps with 16 samples per symbol. The channel has 16 dB loss.

SymbolTime = 100e-12;                  
SamplesPerSymbol = 16;
dbloss = 16;                           

Calculate the sample interval.

dt = SymbolTime/SamplesPerSymbol;

Create the FFE object with fixed mode.

FFEMode = 1;
TapWeights = [0 0.7 -0.2 -0.1];
FFE = serdes.FFE('SymbolTime',SymbolTime,'SampleInterval',dt,...
      'Mode',FFEMode,'WaveType','Sample',...
      'TapWeights',TapWeights);

Create the channel impulse response.

channel = serdes.ChannelLoss('Loss',dbloss,'dt',dt,...
      'TargetFrequency',1/SymbolTime/2);

Create the eye diagram.

eyediagram = comm.EyeDiagram('SampleRate',1/dt,'SamplesPerSymbol',SamplesPerSymbol,...
      'YLimits',[-0.5 0.5]);

Initialize the pseudorandom binary sequence (PRBS) code generator of order 12.

prbsOrder = 12;                         
M = 500;                                %number of symbols to simulate
[dataBit,prbsSeed]=prbs(prbsOrder,1);

Loop through one symbol at a time.

inwave = zeros(SamplesPerSymbol,1);
outwave = zeros(SamplesPerSymbol,1);
for ii = 1:M
      %Get new symbol
      [dataBit,prbsSeed]=prbs(prbsOrder,1,prbsSeed);
      inwave(1:SamplesPerSymbol) = dataBit-0.5;
 
      %convolve input waveform with channel
      y = channel(inwave);
 
      %process one sample at a time through the FFE
      for jj = 1:SamplesPerSymbol
          outwave(jj) = FFE(y(jj));
      end
 
      %Plot eye diagram
      eyediagram(outwave)
end

Extended Capabilities

See Also

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Introduced in R2019a