MER Measurement

Measure modulation error ratio in digital modulation applications

• Library:

• Communications Toolbox / Utility Blocks

• 

Description

The MER Measurement block computes a form of signal-to-noise ratio (SNR) measurement that you can use to assess the ability of a receiver to accurately demodulate a signal. Specifically, it returns the modulation error ratio (MER), minimum MER, and percentile MER for a received signal. You use the MER measurements to determine system performance in communications applications. For example, to determine compliance with applicable DVB-T system radio transmission standards conformance testing requires accurate MER measurements.

This icon shows the block with all ports enabled.

Ports

Input

Ref — Reference signal

scalar | vector | matrix | 3-D array

Reference signal, specified as a scalar, vector, matrix, or 3-D array. If you specify this input, the object measures the MER of the Rcv input by using this input as a reference constellation.

The dimensions of this input must match those of the Rcv input. The object uses each element of this input as the reference symbol for the corresponding element of the Rcv input.

Dependencies

To enable this port, set the Reference signal parameter to Input port.

Data Types: single | double | fixed point
Complex Number Support: Yes

Rcv — Received signal

scalar | vector | matrix | 3-D array

Received signal, specified as a scalar, vector, matrix, or 3-D array.

Data Types: single | double | fixed point
Complex Number Support: Yes

Output

MS — Percentage MER of received signal

scalar

Percentage MER of the received signal over the configured measurement interval, returned as a scalar in units of decibels.

Data Types: double

min — Minimum percentage MER

scalar

Minimum percentage MER over the configured measurement interval, returned as a scalar in units of decibels.

Dependencies

To enable this port, select the Output minimum MER parameter.

Data Types: double

X% — Value below which X% of MER measurements fall

scalar

Value below which X% of MER measurements fall since the last reset, returned as a scalar in units of decibels. Set the value of X in the X-percentile value (%) parameter.

Dependencies

To enable this port, select the Output X-percentile MER parameter.

Data Types: double

nSym — Number of symbols

positive integer

Number of symbols that the object uses to measure the output, returned as a positive integer.

Dependencies

To enable this port, select the Output X-percentile MER and Output the number of symbols processed parameters.

Data Types: double

Parameters

Reference signal — Reference signal source

Input port | Estimated from reference constellation

Reference signal source, specified as Input port or Estimated from reference constellation.

Reference constellation — Reference constellation

constellation(comm.QPSKModulator) (default) | vector

Reference constellation points, specified as a vector.

Dependencies

To enable this parameter, set the Reference signal parameter to Estimated from reference constellation.

Data Types: double
Complex Number Support: Yes

Measurement interval — Measurement interval source

Input length (default) | Entire history | Custom | Custom with periodic reset

Measurement interval source for MER and minimum MER measurements, specified as one of these values.

• Input length — Measure the MER using only the current samples.

• Entire history — Measure the MER for all samples.

• Custom — Measure the MER by using a sliding window over an interval that you specify.

• Custom with periodic reset — Measure the MER over an interval that you specify and reset the block after measuring over each interval.

Custom measurement interval — Custom measurement interval

100 (default) | positive integer

Custom measurement interval in samples, specified as a positive integer.

Dependencies

To enable this parameter, set the Measurement interval parameter to Custom or Custom with periodic reset.

Data Types: double

Averaging dimensions — Averaging dimensions

1 (default) | vector of integers in the range [1, 3]

Dimensions over which the block averages the MER measurements, specified as an integer or row vector of integers in the range [1, 3]. For example, to average across the columns, set this parameter to 2.

This block supports variable-size inputs of the dimensions across which the averaging takes place. However, the input size for the nonaveraged dimensions must remain constant. For example, if the input has size [1000 3 2] and you set this parameter to [1 3], then the output size is [1 3 1] and the number of elements in the second dimension must remain fixed at 3.

Data Types: double

Output minimum MER — Option to add min port to output minimum MER measurements

Off (default) | On

Option to add the min port to output minimum MER measurements. To enable minimum MER measurements, select this parameter.

Output X-percentile MER — Option to add X% port to output X-percentile MER measurements

Off (default) | On

Option to add the X% port to output X-percentile MER measurements. To enable X-percentile MER measurements, select this parameter. When you select this parameter, X-percentile MER measurements persist until you reset the block. The block performs these measurements by using all of the input frames since the last reset. You can set the value of X in the X-percentile value (%) parameter.

X-Percentile value (%) — Value below which X% of MER measurements fall

95 (default) | scalar in the range [0, 100]

Value below which X% of MER measurements fall, specified as a scalar in the range [0, 100].

Dependencies

To enable this parameter, select the Output X-percentile MER parameter.

Data Types: double

Output the number of symbols processed — Option to add nSym port to output number of symbols

Off (default) | On

Option to add the nSym port to output the number of symbols used to measure the X-percentile MER. To measure the number of symbols used for X-percentile MER measurements, select this parameter.

Dependencies

To enable this parameter, select the Output X-percentile MER parameter.

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 than the Code generation option, but the speed of subsequent simulations is slower. 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 C code is reused for subsequent simulations unless the model changes. This option requires additional startup time, but the speed of the subsequent simulations is faster than Interpreted execution.

Model Examples

Measure EVM and MER Using Simulink

Compute error vector magnitude (EVM) and modulation error rate (MER) measurements using Simulink® blocks.

Open Model

Block Characteristics

Data Types	double | fixed point | integer | single
Multidimensional Signals	no
Variable-Size Signals	no

Algorithms

MER is a measure of the SNR in a modulated signal calculated in dB. The MER over a burst containing N symbols is

$$MER=10\times \text{}{\log }_{10}\left(\frac{{\displaystyle \sum _{k=1}^N\left(I_k^2+Q_k^2\right)}}{{\displaystyle \sum _{k=1}^N\left(e_k\right)}}\right)\text{dB,}$$

where:

• e_k = $$e_k={(I_k-{\tilde{I}}_k)}^2+{(Q_k-{\tilde{Q}}_k)}^2$$.

• I_k represents the in-phase component of the kth symbol in the burst.

• Q_k represents the quadrature phase component of the kth symbol in the burst.

• I_k and Q_k represent ideal reference values.

• $${\tilde{I}}_k$$ and $${\tilde{Q}}_k$$ represent received symbols.

• N represents the number of symbols in the burst.

The MER for the kth symbol is

$$ME{R}_k=10\times \text{}{\log }_{10}\left(\frac{\frac{1}{N}{\displaystyle \sum _{k=1}^N\left(I_k^2+Q_k^2\right)}}{e_k}\right)\text{dB}\text{.}$$

The minimum MER represents the minimum MER value in a burst, or

$$ME{R}_{\min }=\underset{k\in [1,\mathrm{...},N]}{\min }\left\{ME{R}_k\right\},$$

The algorithm computes the X-percentile MER by creating a histogram of all the incoming MER_k values. The output provides the MER value above which X% of the MER values fall.

References

[1] ESTI TR 101 290. Digital Video Broadcasting (DVB): Measurement guidelines for DVB systems. June 2020.

Extended Capabilities

C/C++ Code Generation

Generate C and C++ code using Simulink® Coder™.

To generate code in a model using this block, you must enable Dynamic Memory Allocation in MATLAB Functions. For more information, see Dynamic memory allocation in MATLAB functions (Simulink).

Version History

Introduced in R2009b