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comm.GeneralQAMDemodulator

Demodulate using arbitrary QAM constellation

Description

The comm.GeneralQAMDemodulator object demodulates a signal that was modulated using quadrature amplitude modulation. The input is a baseband representation of the modulated signal.

This object accepts variable-size inputs. After the object is locked, you can change the size of each input channel, but you cannot change the number of channels. For more information, see Variable-Size Signal Support with System Objects.

To demodulate a signal that was modulated using quadrature amplitude modulation:

  1. Define and set up your QAM demodulator object. See Construction.

  2. Call step to demodulate a signal according to the properties of comm.GeneralQAMModulator. 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.

Construction

H = comm.GeneralQAMDemodulator creates a demodulator System object, H. This object demodulates the input signal using a general quadrature amplitude modulation (QAM) method.

H = comm.GeneralQAMDemodulator(Name,Value) creates a general QAM demodulator object, H, with each specified property set to the specified value. You can specify additional name-value pair arguments in any order as (Name1,Value1,...,NameN,ValueN).

H = comm.GeneralQAMDemodulator(CONST,Name,Value) creates a general QAM demodulator object, H. This object has the Constellation property set to CONST, and the other specified properties set to the specified values.

Properties

Constellation

Signal constellation

Specify the constellation points as a real or complex, double-precision data type vector. The default is exp(2×π×1i×(0:7)8). The length of the vector determines the modulation order.

When you set the BitOutput property to false, the step method outputs a vector with integer values. These integers are between 0 and M–1, where M is the length of this property vector. The length of the output vector equals the length of the input signal.

When you set the BitOutput property to true, the output signal contains bits. For bit outputs, the size of the signal constellation requires an integer power of two and the output length is an integer multiple of the number of bits per symbol.

BitOutput

Output data as bits

Specify whether the output consists of groups of bits or integer symbol values. The default is false.

When you set this property to true the step method outputs a column vector of bit values with length equal to log2(M) times the number of demodulated symbols, where M is the length of the signal constellation specified in the Constellation property. The length M determines the modulation order.

When you set this property to false, the step method outputs a column vector, of length equal to the input data vector. The vector contains integer symbol values between 0 and M–1.

DecisionMethod

Demodulation decision method

Specify the decision method the object uses as one of Hard decision | Log-likelihood ratio | Approximate log-likelihood ratio. The default is Hard decision. When you set the BitOutput property to false the object always performs hard decision demodulation. This property applies when you set the BitOutput property to true.

VarianceSource

Source of noise variance

Specify the source of the noise variance as one of Property | Input port. The default is Property. This property applies when you set the DecisionMethod property to Log-likelihood ratio or Approximate log-likelihood ratio.

Variance

Noise variance

Specify the variance of the noise as a nonzero, real scalar value. The default is 1.

The LLR algorithm involves computing exponentials of very large or very small numbers using finite precision arithmetic and would yield:

  • Inf to -Inf if the variance is very high

  • NaN if the variance and signal power are both very small

In such cases, use approximate LLR because the algorithm does not involve computing exponentials.

This property applies when you set the VarianceSource property to Property. This property is nontunable for fixed-point inputs.

Tips

The exact LLR algorithm computes exponentials using finite precision arithmetic. For computations involving very large positive or negative magnitudes, the exact LLR algorithm yields:

  • Inf or -Inf if the noise variance is a very large value

  • NaN if the noise variance and signal power are both very small values

The approximate LLR algorithm does not compute exponentials. You can avoid Inf, -Inf, and NaN results by using the approximate LLR algorithm.

OutputDataType

Data type of output

Specify the output data type as one of Full precision | Smallest unsigned integer | double | single | int8 | uint8 | int16 | uint16 | int32 | uint32. The default is Full precision .

This property applies only when you set the BitOutput property to false or when you set the BitOutput property to true and the DecisionMethod property to Hard decision or Approximate log-likelihood ratio. In this case, when you set the OutputDataType property to Full precision, the output data type is the same as that of the input when the input data has a single or double-precision data type.

When the input data is of a fixed-point type, the output data type works as if you had set the OutputDataType property to Smallest unsigned integer.

When the input signal is an integer data type, you must have a Fixed-Point Designer™ user license to use this property in Smallest unsigned integer or Full precision mode.

When you set the BitOutput property to true, and the DecisionMethod property to Hard Decision the data type logical becomes a valid option.

When you set the BitOutput property to true and the DecisionMethod property to Approximate log-likelihood ratio you may only set this property to Full precision | Custom.

If you set the BitOutput property to true and the DecisionMethod property to Log-likelihood ratio, the output data has the same type as that of the input. In this case, that value can be only single or double precision.

 Fixed-Point Properties

Methods

stepDemodulate using arbitrary QAM constellation
Common to All System Objects
release

Allow System object property value changes

Examples

Modulate and demodulate data using an arbitrary three-point constellation.

 % Setup a three point constellation
 c = [1 1i -1];
 hQAMMod = comm.GeneralQAMModulator(c);
 hAWGN = comm.AWGNChannel('NoiseMethod', ...
     'Signal to noise ratio (SNR)','SNR',15,'SignalPower',0.89);
 hQAMDemod = comm.GeneralQAMDemodulator(c);

 %Create an error rate calculator
 hError = comm.ErrorRate;
 for counter = 1:100
     % Transmit a 50-symbol frame
     data = randi([0 2],50,1);
     modSignal = step(hQAMMod, data);
     noisySignal = step(hAWGN, modSignal);
     receivedData = step(hQAMDemod, noisySignal);
     errorStats = step(hError, data, receivedData);
 end
 fprintf('Error rate = %f\nNumber of errors = %d\n', ...
      errorStats(1), errorStats(2))

More About

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Algorithms

This object implements the algorithm, inputs, and outputs described on the General QAM Demodulator Baseband block reference page. The object properties correspond to the block parameters.

Extended Capabilities

Version History

Introduced in R2012a