MIL-188 QAM Demodulator Baseband

R2026b

MIL-STD-188-110 B/C standard-specific quadrature amplitude demodulation

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MIL-188 QAM Demodulator Baseband block

To add a block to a model, double-click the canvas and start typing the block name. Then, select the block from the list.

Libraries:
Communications Toolbox / Modulation / Digital Baseband Modulation / AM
Communications Toolbox / Modulation / Digital Baseband Modulation / Standard-Compliant

Description

The MIL-188 QAM Demodulator Baseband block demodulates the input signal using MIL-STD-188-110 standard-specific quadrature amplitude modulation (QAM). For a description of MIL-STD-188 compliant demodulation, see MIL-STD-188-110 QAM Hard Demodulation and MIL-STD-188-110 QAM Soft Demodulation.

This icon shows the block with all ports enabled:

Examples

Demodulate Noisy MIL-STD-188 QAM Signal

Apply MIL-STD-188 QAM modulation to a signal of random data. Pass the modulated signal through an AWGN channel. Demodulate the noisy MIL-STD-188 QAM signal. Check the bit error rate (BER).

Run the slex_mil188_qam_demod model with the EbN0 of the AWGN channel block set to 6 dB. The results are saved to the base workspace variable ErrorVec in a 1-by-3 row vector. The first element contains the BER.

With EbN0 set to 6 dB, BER: 0.636

Change the EbN0 of the AWGN channel block to 10 dB. Run the model and observe the decrease in BER.

With EbN0 set to 10 dB, BER: 0.545

Ports

Input

In — MIL-STD-188 standard-specific QAM modulated signal

scalar | vector | matrix

MIL-STD-188 standard-specific QAM modulated signal, specified as a scalar, vector, or matrix. When this input is a matrix, each column is treated as an independent channel. This port is unnamed until the Var port is enabled.

Data Types: double | single
Complex Number Support: Yes

Var — Noise variance

positive scalar | vector of positive values

Noise variance, specified as a positive scalar or vector of positive values. When the noise variance or signal power result in computations involving extreme positive or negative magnitudes, see MIL-STD-188-110 QAM Soft Demodulation for demodulation decision type considerations.

Dependencies

To enable this port set the Noise variance source parameter to Input port.

Output

Out — Demodulated signal

scalar | vector | matrix

Demodulated signal, returned as a scalar, vector, or matrix. The dimensions of the demodulated signal depend on the specified Output type and Decision type parameter values. This port is unnamed on the block.

Output type	Decision type	Demodulated Signal Description	Dimensions of Demodulated Signal
Integer	—	Demodulated integer values in the range [0, (M – 1)]	The output signal has the same dimensions as input signal.
Bit	Hard decision	Demodulated bits	The number of rows in the output signal is log2(M) times the number of rows in the input signal. Each demodulated symbol is mapped to a group of log2(M) elements in a column, where the first element represents the MSB, and the last element represents the LSB.
	Log-likelihood ratio	Log-likelihood ratio value for each bit
	Approximate log-likelihood ratio	Approximate log-likelihood ratio value for each bit
M is the value of Modulation order.

Use Output data type to specify the output data type.

Parameters

To edit block parameters interactively, use the Property Inspector. From the Simulink^® Toolstrip, on the Simulation tab, in the Prepare gallery, select Property Inspector.

Modulation order — Modulation order

16 (default) | 32 | 64 | 256

Modulation order, M, specified as 16, 32, 64, or 256. The modulation order specifies the total number of points in the constellation of the input signal.

Constellation scaling — Constellation scaling

As specified in standard (default) | Unit average power

Constellation scaling, specified as:

• As specified in standard – The block scales the constellation based on specifications in the relevant standard [1].

• Unit average power – The block scales the constellation to an average power of 1 watt referenced to 1 ohm.

Output type — Input type

Integer (default) | Bit

Output type, specified as Integer or Bit. To use Integer, the input signal must consist of integers in the range [0, (M – 1)]. To use Bit, the input signal must contain binary values, and the number of rows must be an integer multiple of log₂(M), where M is the Modulation order.

Decision type — Demodulation decision type

Hard decision (default) | Log-likelihood ratio | Approximate log-likelihood ratio

Demodulation decision type, specified as Hard decision, Log-likelihood ratio, or Approximate log-likelihood ratio. See MIL-STD-188-110 QAM Soft Demodulation for algorithm selection considerations.

Dependencies

This parameter applies when you set Output type to Bit.

Noise variance source — Noise variance source

Property (default) | Input port

Noise variance source, specified as:

• Property — Set the noise variance using the Noise variance parameter.

• Input port — Set the noise variance using the Var input port.

Dependencies

This parameter applies when you set Decision type to either Log-likelihood ratio or Approximate log-likelihood ratio.

Noise variance — Noise variance

1 (default) | positive scalar | vector of positive values

Noise variance, specified as a positive scalar or vector of positive values.

• When specified as a scalar, that value is used on all elements in the input signal.

• When specified as a vector, the vector length must be equal to the number of columns in the input signal. Each noise variance vector element is applied to its corresponding column in the input signal.

Dependencies

This parameter applies when you set Noise variance to Property and Decision type to either Log-likelihood ratio or Approximate log-likelihood ratio.

Output data type — Output data type

double (default) | ...

Output data type, specified as one of the acceptable values from this table. Acceptable Output data type values depend on the Output type and Decision type parameter values.

Output type	Decision type	Output data type Options
Integer	Not applicable	double, single, int8, uint8, int16, uint16, int32, or uint32
Bit	Hard decision	double, single, int8, uint8, int16, uint16, int32, uint32, or logical
	Log-likelihood ratio or Approximate log-likelihood ratio	The output signal is the same data type as the input signal.

Dependencies

This parameter applies when you set Output type to Integer or when you set Output type to Bit and Decision type to Hard decision.

Simulate using — Type of simulation to run

Interpreted execution (default) | Code generation

Type of simulation to run, specified as Interpreted execution or Code generation.

• Interpreted execution — Simulate the model by using the MATLAB^® interpreter. This option requires less startup time, but the speed of subsequent simulations is slower than with the Code generation option. In this mode, you can debug the source code of the block.

• Code generation — Simulate the model by using generated C code. The first time you run a simulation, Simulink generates C code for the block. The model reuses the C code for subsequent simulations unless the model changes. This option requires additional startup time, but the speed of the subsequent simulations is faster than with the Interpreted execution option.

For more information, see Interpreted Execution vs. Code Generation (Simulink).

Block Characteristics

Data Types	Boolean | double | integer | single
Multidimensional Signals	yes
Variable-Size Signals	no

Programmatic Use: Add Block

To add the block programmatically, use the add_block function with one of these library block paths as the source.

"commdigbbndam3/MIL-188 QAM Demodulator Baseband"

"commdigbbndstd/MIL-188 QAM Demodulator Baseband"

Example: add_block("commdigbbndam3/MIL-188 QAM Demodulator Baseband","myModel/myBlock",MakeNameUnique="on")

More About

MIL-STD-188-110

MIL-STD-188-110 is a US Department of Defense standard for HF communications using serial PSK mode of both data and voice signals.

The standard specifies physical layer modulation schemes for tactical and long-haul communications. The modulation scheme specified by the standard is a mix of QAM and APSK. For a detailed description of the modulation scheme, see [1].

MIL-STD-188-110 QAM Hard Demodulation

The hard demodulation algorithm uses optimum decision region-based demodulation. Since all the constellation points are equally probable, maximum a posteriori probability (MAP) detection reduces to a maximum likelihood (ML) detection. The ML detection rule is equivalent to choosing the closest constellation point to the received symbol. The decision region for each constellation point is designed by drawing perpendicular bisectors between adjacent points. A received symbol is mapped to the proper constellation point based on which decision region it lies in.

Since all MIL-STD constellations are quadrant-based symmetric, for each symbol the optimum decision region-based demodulation:

• Maps the received symbol into the first quadrant

• Chooses the decision region for the symbol

• Maps the constellation point back to its original quadrant using the sign of real and imaginary parts of the received symbol

MIL-STD-188-110 QAM Soft Demodulation

For soft demodulation, two soft-decision log-likelihood ratio (LLR) algorithms are available: exact LLR and approximate LLR. The exact LLR algorithm is more accurate but has slower execution speed than the approximate LLR algorithm. For further description of these algorithms, see the Hard- vs. Soft-Decision Demodulation topic.

Tips

• For faster execution of the MIL-188 QAM Demodulator Baseband block, set the Simulate using parameter to:

  • Code generation when using hard decision demodulation.

  • Interpreted execution when using soft decision demodulation.

References

[1] MIL-STD-188-110B & C: "Interoperability and Performance Standards for Data Modems." Department of Defense Interface Standard, USA.

Extended Capabilities

C/C++ Code Generation
Generate C and C++ code using Simulink® Coder™.

Version History

Introduced in R2018b

R2026b: Update exact LLR algorithm to use LogSumExp for improved numerical stability

Starting in R2026b, the exact LLR algorithm uses LogSumExp for improved numerical stability, returning finite values for extreme noise variance or signal power conditions. Previously, outputs could be Inf, –Inf, or NaN in these cases. For more information, see Exact LLR Algorithm.