Measure modulation error ratio
The comm.MER
(modulation error ratio) object
measures the signaltonoise ratio (SNR) in digital modulation applications.
You can use MER measurements to determine system performance in communications
applications. For example, determining whether a DVBT system conforms
to applicable radio transmission standards requires accurate MER measurements.
The block measures all outputs in dB.
To measure modulation error ratio:
Define and set up your MER object. See Construction.
Call step
to measure the modulation error ratio
according to the properties of comm.MER
. 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.
MER = comm.MER
creates a modulation error
ratio (MER) System object, MER
. This object
measures the signaltonoise ratio (SNR) in digital modulation applications.
MER = comm.MER(
creates
an Name
,Value
)MER
object with each specified property set
to the specified value. You can specify additional namevalue pair
arguments in any order as (Name1
,Value1
,...,NameN
,ValueN
).
Example: MER = comm.MER('ReferenceSignalSource','Estimated
from reference constellation')
creates an object, MER
,
that measures the MER of a received signal by using a reference constellation.

Reference signal source Reference signal source, specified as either 

Reference constellation Reference constellation, specified as a vector. This property
is available when the The default is 

Measurement interval source Measurement interval source, specified as one of the following:


Measurement interval Measurement interval over which the MER is calculated, specified
in samples as a real positive integer. This property is available
when 

Averaging dimensions Averaging dimensions, specified as a positive integer or row
vector of positive integers. This property determines the dimensions
over which the averaging is performed. For example, to average across
the rows, set this property to The object supports variablesize inputs over the dimensions
in which the averaging takes place. However, the input size for the
nonaveraged dimensions must remain constant between 

Minimum MER measurement output port Minimum MER measurement output port, specified as a logical
scalar. To create an output port for minimum MER measurements, set
this property to 

Xpercentile MER measurement output port Xpercentile MER measurement output port,
specified as a logical scalar. To create an output port for Xpercentile
MER measurements, set this property to 

Xpercentile value Xpercentile value above which X%
of the MER measurements fall, specified as a real scalar from 

Symbol count output port Symbol count output port, specified as a logical scalar. To
output the number of accumulated symbols used to calculate the Xpercentile
MER measurements, set this property to 
step  Measure modulation error ratio 
MER is a measure of the SNR in a modulated signal calculated in dB. The MER over N symbols is
$$\text{MER}=10\xb7\text{}{\mathrm{log}}_{10}\left(\frac{{\displaystyle \sum _{n=1}^{N}\left({I}_{k}^{2}+{Q}_{k}^{2}\right)}}{{\displaystyle \sum _{n=1}^{N}\left({e}_{k}\right)}}\right)\text{\hspace{0.17em}}\text{dB,}$$
The MER for the kth symbol is
$$ME{R}_{k}=10*\text{}{\mathrm{log}}_{10}\left(\frac{\frac{1}{N}{\displaystyle \sum _{n=1}^{N}\left({I}_{k}^{2}+{Q}_{k}^{2}\right)}}{{e}_{k}}\right)\text{\hspace{0.17em}}\text{dB}\text{.}$$
The minimum MER represents the minimum MER value in a burst, or
$$ME{R}_{\mathrm{min}}=\underset{k\in [1,\mathrm{...},N]}{\mathrm{min}}\left\{ME{R}_{k}\right\}\text{\hspace{0.17em}},$$
where:
e_{k} = $${e}_{k}={({I}_{k}{\tilde{I}}_{k})}^{2}+{({Q}_{k}{\tilde{Q}}_{k})}^{2}$$
I_{k} = Inphase measurement of the kth symbol in the burst
Q_{k} = Quadrature phase measurement of the kth symbol in the burst
I_{k} and Q_{k} represent ideal (reference) values. $${\tilde{I}}_{k}$$ and $${\tilde{Q}}_{k}$$ represent measured (received) symbols.
The block computes the Xpercentile 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.