Implement Upsampler for HDL

This example shows how to use the Upsampler block to upsample data. This block supports scalar and vector inputs. You can generate HDL code from the subsystem used in this example.

Set Up Input Data Parameters

Set up workspace variables for the Simulink® model to use. These variables configure the Upsampler block inside the subsystem.

L = 8;                   % Upsample factor
O = 0;                   % Sample offset

scalar = true;
if scalar
    vecSize = 1;
    outSize = 1;
    minCycles = L;
else
    vecSize = 16;   %#ok % Vector size must be a multiple or factor of L
    outSize = vecSize*L;
    minCycles = 1;
end

Generate Reference Data from Function

Generate frames of random input samples and apply the upsample function. Use the output as reference data against which to compare the output of the block.

totalsamples = 0;
numFrames =1;
dataSamples = cell(1,numFrames);
framesize = zeros(1,numFrames);
refOutput = [];
WL = 0;            % Word length
FL = 0;            % Fraction length

for i = 1:numFrames
    framesize(i) = randi([5 200],1,1);
    dataSamples{i} = fi(randn(vecSize,framesize(i)),1,16,8);
    ref_upsample= upsample((dataSamples{i}(:)),L,O);
    refOutput = [refOutput,ref_upsample]; %#ok
end

Run Model

Run the model to import the input signal variables from the MATLAB® workspace to the Upsampler block in the model. Insert the required number of idle cycles after each frame using the latency variable to avoid invalid output data. Initialize the size of the output to accommodate the output data.

latency = 3;
sampleIn = zeros(vecSize,size(dataSamples{i},2)*minCycles);
validIn = upsample(true(1,length(dataSamples{i})),minCycles);
sampleIn(:,validIn) = dataSamples{i};

sampletime = 1;
simTime = length(validIn)+latency;

modelname = "HDLUpsampler";
open_system(modelname);
sim(modelname);

Compare Block Output with Function Output

Compare the output of the block with the output of the Upsampler function.

sampleOut = squeeze(sampleOut_ts.Data);
validOut  = squeeze(validOut_ts.Data);
if scalar
    HDLOutput = sampleOut(validOut);
else
    HDLOutput = sampleOut(:,validOut); %#ok
end
HDLOutput = HDLOutput(:);

fprintf('Upsampler\n');
difference = (abs(HDLOutput-refOutput(1:length(HDLOutput)))>0);
fprintf(['\nTotal number of samples differed between Behavioral ' ...
    'and HDL simulation: %d \n'],sum(difference));

Upsampler

Total number of samples differed between Behavioral and HDL simulation: 0