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Diffstat (limited to 'doc/thesis/chapters/implementation.tex')
| -rw-r--r-- | doc/thesis/chapters/implementation.tex | 18 |
1 files changed, 13 insertions, 5 deletions
diff --git a/doc/thesis/chapters/implementation.tex b/doc/thesis/chapters/implementation.tex index ff073ee..9a20d24 100644 --- a/doc/thesis/chapters/implementation.tex +++ b/doc/thesis/chapters/implementation.tex @@ -341,10 +341,21 @@ Rician fading factor K = 0 = Rylehnt Model \subsection{Measurements} +\skelpar[5]{ + Do some masurements +} + \subsection{Empirical BER} \label{sec:ber} -To find out how accurate the simulations are comparer with a simulation of the fadinng effect and test measurements, the byte error rate of the system is calculated. This is done with the help of a user specified \(k\)-byte test frame in the beginning of each vector. Implemented according to the code in \ref{lst:ber-block}. Every bit is compared with the test vector at the beginning before the modulation and demodulation part. -Because of the fact that the test vector has some random bit at the end the bit error rate has always a value on average 32. +To find out how accurate the simulations are comparer with a simulation of the fadinng effect and tested measurements, the byte error rate of the system is calculated. This is done with the help of a user specified \(k\)-byte test frame in the beginning of each vector. Implemented according to the code in \ref{lst:ber-block}. Every bit is compared with the test vector at the beginning before the modulation and demodulation part. +Because of the fact that the test vector has some random bit at the end the bit error rate has always a value on average 32, even when its perfect match. So to avoid high numbers this value is subtracted and only on focused on the positive values. + +The vector which is used as test vector is: \([0x1f, 0x35] + [0x12, 0x48] \), because this numbers are well suited to compare. +For generating the Byte error rate it is focus on byte-blocks of a specific length. So for each of this blocks compared with test vector there is a BER. To make it simpler or better said to avoid mistakes, the last 200 of this individual BER are taken to find an average and the highest value. + +\skelpar[5]{ + Maybe more +} @@ -380,9 +391,6 @@ Because of the fact that the test vector has some random bit at the end the bit -\skelpar[5]{ - Discuss how i did that -} \begin{figure} |