In real world the index η is always less than 1. The closer η to 1, the more perfect
system of information transmission.
A large enough contribution to the information efficiency brings the multiplier
. On the one hand, large positional modulation can transmit more information in
the same frequency band Δ
; on the other hand, it reduces the necessary reliability and
leads to the use of a more powerful error-correcting code.
There is no doubt that the choice of the optimal MCS depends on the SNR in
communication channel. Based on this factor, let’s define the SNR bounds as
[ℎ
2
,ℎ
2
] for evaluating the information efficiency at the demodulator input, and
calculate the information efficiency for each MCS and see the greatest efficiency value
and respective
ℎ
2
value.
Let’s suppose we want to ensure the reliability (BER) on the decoder output on
the level
=10
−6
.
To construct the graph of information efficiency dependence from SNR values,
the data were taken from work, namely SER values for each modulation type.
Next, for each SER value, the rate r
C
identified for existing error-correcting code.
Then, for each SNR value, calculating the multiplication value of code rate and
modulation index m.
The next step determines the intersection points of productivity and coding rate.
For each multiplication value of code rate and modulations information
capacity QPSK, QAM-16, QAM-64 and QAM-256, there are corresponding separate
error-correcting code gradations velocities on Fig. 5, as follows: 1/2, 3/5, 2/3, 3/4, 4/5,
5/6. These steps correspond to the point of switching the modulation types.
Figure 5. A plot of multiplication the code code rate and signal construction
informational capacity (
) as a function of SNR (ℎ
2
)
Source: developed by the author
It is advisable to draw the conclusion that we should move on to signals with
higher modulation multiplicity and use appropriate code rates, given the fact of
increasing the power, under certain SNR threshold.
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