General QAM Demodulator Baseband
Demodulate QAMmodulated data
Library
AM, in Digital Baseband sublibrary of Modulation
Description
The General QAM Demodulator Baseband block demodulates a signal that was modulated using quadrature amplitude modulation. The input is a baseband representation of the modulated signal.
The input must be a discretetime complex signal. The Signal constellation parameter defines the constellation by listing its points in a lengthM vector of complex numbers. The block maps the mth point in the Signal constellation vector to the integer m1.
This block accepts a scalar or column vector input signal. For information about the data types each block port supports, see the Supported Data Types table on this page.
Parameters
 Signal constellation
A real or complex vector that lists the constellation points.
 Output type
Determines whether the block produces integers or binary representations of integers.
If you set this parameter to
Integer
, the block produces integers.If you set this parameter to
Bit
, the block produces a group of K bits, called a binary word, for each symbol, when Decision type is set toHard decision
. If Decision type is set toLoglikelihood ratio
orApproximate loglikelihood ratio
, the block outputs bitwise LLR and approximate LLR, respectively. Decision type
Specifies the use of hard decision, LLR, or approximate LLR during demodulation. For more information, see Hard vs. SoftDecision Demodulation.
To enable this parameter, set Output type to
Bit
. Variance source
When you set this parameter to
Dialog
, you can then specify the noise variance in the Variance parameter. When you set this option toPort
, a port appears on the block through which the noise variance can be input.To enable this parameter, set Decision type to
Approximate loglikelihood ratio
orLoglikelihood ratio
. Variance
This parameter appears when the Variance source is set to
Dialog
and specifies the noise variance in the input signal. This parameter is tunable in normal mode, Accelerator mode, and Rapid Accelerator mode. This parameter is nontunable for fixedpoint inputs.If you use the Simulink^{®} Coder™ rapid simulation (RSIM) target to build an RSIM executable, then you can tune the parameter without recompiling the model. This is useful for Monte Carlo simulations in which you run the simulation multiple times (perhaps on multiple computers) with different amounts of noise.
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
orInf
if the noise variance is a very large valueNaN
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
, andNaN
results by using the approximate LLR algorithm.
FixedPoint Signal Flow Diagrams
FixedPoint Signal Flow Diagram for Hard Decision Mode
Note
In the figure above, M represents the size of the Signal constellation.
The general QAM Demodulator Baseband block
supports fixedpoint operations for computing hard decision (Output
type set to Bit
and Decision
type is set to Hard decision
) and
approximate LLR (Output type is set to
Bit
and Decision type is set
to Approximate loglikelihood ratio
) output values. The
input values must have fixedpoint data type for fixedpoint operations.
Note
Fixedpoint operations are NOT yet supported for exact LLR output values.
FixedPoint Signal Flow Diagram for Approximate LLR Mode
Note
In the figure above, M represents the size of the Signal constellation.
FixedPoint Signal Flow Diagram for Approximate LLR Mode: Noise Variance Operation Modes
Note
If Variance source is set to
Dialog
, the block performs the operations
shown inside the dotted line once during initialization. The block also
performs these operations if the Variance value changes
during simulation.
Data Types Attributes
 Output
The block supports the following Output options:
When you set the parameter to
Inherit via internal rule
(default setting), the block inherits the output data type from the input port. The output data type is the same as the input data type if the input is of typesingle
ordouble
.For integer outputs, you can set this block's output to
Inherit via internal rule
(default setting),Smallest unsigned integer
,int8
,uint8
,int16
,uint16
,int32
,uint32
,single
, anddouble
.For bit outputs, when you set Decision type to
Hard decision
, you can set the output toInherit via internal rule
,Smallest unsigned integer
,int8
,uint8
,int16
,uint16
,int32
,uint32
,boolean
,single
, ordouble
.When you set Decision type to
Hard decision
orApproximate loglikelihood ratio
and the input is a floating point data type, then the output inherits its data type from the input. For example, if the input is of data typedouble
, the output is also of data typedouble
. When you set Decision type toHard decision
orApproximate loglikelihood ratio
, and the input is a fixedpoint signal, the Output parameter, located in the FixedPoint algorithm parameters region of the DataType tab, specifies the output data type.When you set the parameter to
Smallest unsigned integer
, the output data type is selected based on the settings used in the Hardware Implementation pane of the Configuration Parameters dialog box. If you selectASIC/FPGA
in the Hardware Implementation pane, the output data type is the ideal minimum size, i.e.,ufix(1)
for bit outputs, and $$ufix\left(\lceil {\mathrm{log}}_{2}M\rceil \right)$$ for integer outputs. For all other choices, the Output data type is an unsigned integer with the smallest available word length large enough to fit the ideal minimum size, usually corresponding to the size of a char (e.g.,uint8
). Rounding Mode Parameter
Use this parameter to specify the rounding method to be used when the result of a fixedpoint calculation does not map exactly to a number representable by the data type and scaling storing the result.
For more information, see Rounding Modes or Rounding Mode: Simplest (FixedPoint Designer).
 Saturate on integer overflow
Use this parameter to specify the method to be used if the magnitude of a fixedpoint calculation result does not fit into the range of the data type and scaling that stores the result:
Saturate represents positive overflows as the largest positive number in the range being used, and negative overflows as the largest negative number in the range being used.
Wrap uses modulo arithmetic to cast an overflow back into the representable range of the data type. See Modulo Arithmetic (FixedPoint Designer) for more information.
For more information, see the Saturate on integer overflow parameter subsection of Specify FixedPoint Attributes for Blocks.
 Signal constellation
Use this parameter to define the data type of the Signal constellation parameter.
When you select
Same word length as input
the word length of the Signal constellation parameter matches that of the input to the block. The fraction length is computed to provide the best precision for given signal constellation values.Select
Specify word length
, to enable Word Length parameter, and then you can modify the word length. The fraction length is computed to provide the best precision for given signal constellation values.
 Accumulator 1
Use this parameter to specify the data type for Accumulator 1:
When you select
Inherit via internal rule
, the block automatically calculates the output word and fraction lengths. For more information, see Inherit via Internal Rule.When you select
Binary point scaling
, you can enter the word length and the fraction length of Accumulator 1, in bits.
 Product Input
Use this parameter to specify the data type for Product input.
When you select
Same as accumulator 1
, the Product Input characteristics match those of Accumulator 1.When you select
Binary point scaling
you can enter the word length and the fraction length of Product input, in bits.
 Product Output
Use this parameter to select the data type for Product output.
When you select
Inherit via internal rule
, the block automatically calculates the output signal type. For more information, see Inherit via Internal Rule.When you select
Binary point scaling
enter the word length and the fraction length for Product output, in bits.
 Accumulator 2
Use this parameter to specify the data type for Accumulator 2:
When you select
Inherit via internal rule
, the block automatically calculates the accumulator data type. The internal rule calculates the ideal, fullprecision word length and fraction length as follows:WL_{ideal accumulator 2} = WL_{input to accumulator 2}
FL_{ideal accumulator 2} = FL _{input to accumulator 2}
After the fullprecision result is calculated, your particular hardware may still affect the final word and fraction lengths set by the internal rule. For more information, see The Effect of the Hardware Implementation Pane on the Internal Rule.
The internal rule always sets the sign of datatype to
Unsigned
.When you select
Binary point scaling
, you are able to enter the word length and the fraction length of Accumulator 2, in bits.
The settings for the following fixedpoint
parameters only apply when you set
Decision type to
Approximate loglikelihood
ratio
.
 Accumulator 3
When you select
Inherit via internal rule
, the block automatically calculates the accumulator data type. The internal rule first calculates ideal, fullprecision word length and fraction length as follows:WL_{ideal accumulator 3} = WL_{input to accumulator 3} + 1
FL _{ideal accumulator 3} = FL _{input to accumulator 3}.
After the fullprecision result is calculated, your particular hardware may still affect the final word and fraction lengths set by the internal rule. For more information, see The Effect of the Hardware Implementation Pane on the Internal Rule.
The internal rule always sets the sign of datatype to
Signed
. Noise scaling input
When you select
Same as accumulator 3
, the Noise scaling input characteristics match those of Accumulator 3.When you select
Binary point scaling
you are able to enter the word length and the fraction length of Noise scaling input, in bits.
 Inverse noise variance
To enable this parameter, set Variance source to
Dialog
. This parameter appears in the Data Types tab.When you select
Same word length as input
the word length of the Inverse noise variance parameter matches that of the input to the block. The fraction length is computed to provide the best precision for a given inverse noise variance value.When you select
Specify word length
, the Word Length parameter appears, and then you can modify the word length. The fraction length is computed to provide the best precision for a given inverse noise variance value.
 Output
When you select
Inherit via internal rule
, the Output data type is automatically set for you.If you set the Variance source parameter to
Dialog
, the output is a result of product operation as shown in the Noise Variance Operation Modes Signal Flow Diagram FixedPoint Signal Flow Diagram for Approximate LLR Mode: Noise Variance Operation Modes. In this case, it follows the internal rule for Product data types specified in the Inherit via Internal Rule topic.If the Variance source parameter is set to
Port
, the output is a result of division operation as shown in the signal flow diagram. In this case, the internal rule calculates the ideal, fullprecision word length and fraction length as follows:WL _{output} = max(WL _{Noise scaling input}, WL_{ Noise variance})
FL _{output} = FL _{Noise scaling input (dividend)}– FL _{Noise variance (divisor)} .
After the fullprecision result is calculated, your particular hardware may still affect the final word and fraction lengths set by the internal rule. For more information, see The Effect of the Hardware Implementation Pane on the Internal Rule.
The internal rule for Output always sets the sign of datatype to
Signed
.
For additional information about the parameters pertaining to fixedpoint applications, see Specify FixedPoint Attributes for Blocks.
Supported Data Types
Port  Supported Data Types 

Input 

Var 

Output 

Pair Block
Extended Capabilities
Version History
Introduced before R2006a