Question: Question 2 ( 7 0 pts ) In Matlab, the trellis diagram for the 1 st row of Table 7 . 4 ( Constraint Length,
Question pts
In Matlab, the trellis diagram for the st row of Table Constraint Length, and rate code
can be stated as follows,
trellis polytrellis
a pts Plot the simulated BER for the coded BPSK system for rate convolutionally code
with constraint lengths and respectively. You can generate Million
information bits, varies between to and set the zero mean Gaussian channel
noise variance is
b pts For Hard decision decoding HDD plot the coded BER for each value of and its
BER upperbound. You can use "bercoding" command to compute the coded BER
upperbound. For a given is it a good idea to use the BER upperbound when the simulated
BER is not available? Comment on your results. To compute the upperbound, you can use
"distspectrellis
c pts Plot execution time of the Viterbi decoder for million information bits for each
value of given in Q part a Hint: You can use tic, toc commands or see etime function.
d pts Now you should seek the performance of soft decision decoding SDD instead of
HDD You should partition the interval between and into intervals.
As an example, for you can set the decision thresholds as or for you
can set the decision thresholds as and so on Let be a soft
decision bit level sample, then is obtained from the received coded BPSK symbol
from,
To obtain the quantized soft decisions from the received coded BPSK symbolds, you can use
the function "quantiz". Then, for a rate convolutional code with obtain the BER and
BER upperbound for SDD Also compare your results with BER and its upperbound for HDD
Comment on your results.
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