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comm.gpu.LDPCDecoder System object

Package: comm

Decode binary low-density parity-check data with GPU


The GPU LDPCDecoder object decodes a binary low-density parity-check code using a graphics processing unit (GPU).

    Note:   To use this object, you must install a Parallel Computing Toolbox™ license and have access to an appropriate GPU. For more about GPUs, see GPU Computing in the Parallel Computing Toolbox documentation.

A GPU-based System object™ accepts typical MATLAB® arrays or objects that you create using the gpuArray class as an input. GPU-based System objects support input signals with double- or single-precision data types. The output signal inherits its datatype from the input signal.

  • If the input signal is a MATLAB array, then the output signal is also a MATLAB array. In this case, the System object handles data transfer between the CPU and GPU.

  • If the input signal is a gpuArray, then the output signal is also a gpuArray. In this case, the data remains on the GPU. Therefore, when the object is given a gpuArray, calculations take place entirely on the GPU and no data transfer occurs. Passing gpuArray arguments provides increased performance by reducing simulation time. For more information, see Establish Arrays on a GPU in the Parallel Computing Toolbox documentation.

To decode a binary low-density parity-check code:

  1. Define and set up your binary low-density parity-check decoder object. See Construction.

  2. Call step to decode a binary low-density parity-check code according to the properties of comm.gpu.LDPCDecoder. The behavior of step is specific to each object in the toolbox.

    Note:   Starting in R2016b, instead of using the step method to perform the operation defined by the System object, you can call the object with arguments, as if it were a function. For example, y = step(obj,x) and y = obj(x) perform equivalent operations.


h = comm.gpu.LDPCDecoder creates a GPU-based LDPC binary low-density parity-check decoder object, h. This object performs LDPC decoding based on the specified parity-check matrix. The object does not assume any patterns in the parity-check matrix.

h = comm.gpu.LDPCDecoder('PropertyName','ValueName') creates a GPU-based LDPC decoder object, h, with each specified property set to the specified value. You can specify additional name-value pair arguments in any order as ('PropertyName1','PropertyValue1',...,'PropertyNameN','PropertyValueN').

h = comm.gpu.LDPCDecoder(PARITY) creates a GPU-based LDPC decoder object, h, with the ParityCheckMatrix property set to PARITY.



Parity-check matrix

Specify the parity-check matrix as a binary valued sparse matrix with dimension (N-by-K) by N, where N > K > 0. The last N−K columns in the parity check matrix must be an invertible matrix in GF(2). This property accepts numeric or logical data types. The upper bound for the value of N is (231)-1. The default is the parity-check matrix of the half-rate LDPC code from the DVB-S.2 standard, which is the result of dvbs2ldpc(1/2).


Select output value format

Specify the output value format as one of Information part | Whole codeword. The default is Information part. When you set this property to Information part, the output contains only the message bits and is a multiple of K length column vector, assuming an (N-by-K)xK parity check matrix. When you set this property to Whole codeword, the output contains the codeword bits and is an N element column vector.


Decision method

Specify the decision method used for decoding as one of Hard decision | Soft decision. The default is Hard decision. When you set this property to Hard decision, the output is decoded bits of logical data type. When you set this property to Soft decision, the output is log-likelihood ratios of single or double data type.


Maximum number of decoding iterations

Specify the maximum number of iterations the object uses as an integer valued numeric scalar. The default is 50.


Condition for iteration termination

Specify the condition to stop the decoding iterations as one of Maximum iteration count | Parity check satisfied. The default is Maximum iteration count. When you set this property to Maximum iteration count, the object will iterate for the number of iterations you specify in the MaximumIterationCount property. When you set this property to Parity check satisfied, the object will determine if the parity checks are satisfied after each iteration and stops if all parity checks are satisfied.


Output number of iterations performed

Set this property to true to output the actual number of iterations the object performed. The default is false.


Output final parity checks

Set this property to true to output the final parity checks the object calculated. The default is false.


cloneCreate GPU LDPC Decoder object with same property values
isLockedLocked status for input attributes and nontunable properties
releaseAllow property value and input characteristics changes
stepDecode input signal using LDPC decoding scheme


The GPU LDPC Decoder System object uses the same algorithm as the LDPC Decoder block. See Decoding Algorithm for details.


Transmit an LDPC-encoded, QPSK-modulated bit stream through an AWGN channel, then demodulate, decode, and count errors.

    hEnc = comm.LDPCEncoder;
    hMod = comm.PSKModulator(4, 'BitInput',true);
    hChan = comm.AWGNChannel(...
            'NoiseMethod','Signal to noise ratio (SNR)','SNR',1);
    hDemod = comm.PSKDemodulator(4, 'BitOutput',true,...
            'DecisionMethod','Approximate log-likelihood ratio', ...
            'Variance', 1/10^(hChan.SNR/10));
    hDec = comm.gpu.LDPCDecoder;
    hError = comm.ErrorRate;
    for counter = 1:10
      data           = logical(randi([0 1], 32400, 1));
      encodedData    = step(hEnc, data);
      modSignal      = step(hMod, encodedData);
      receivedSignal = step(hChan, modSignal);
      demodSignal    = step(hDemod, receivedSignal);
      receivedBits   = step(hDec, demodSignal);
      errorStats     = step(hError, data, receivedBits);
    fprintf('Error rate       = %1.2f\nNumber of errors = %d\n', ...
      errorStats(1), errorStats(2))

Introduced in R2012a

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