# Evaluation of the Digital Data Performance Transmission on a Fiber-Radio System
## 3 Simulation Results
### Wireless Transmission Results  
The saved data of the optical transmission stage are used to validate the wireless transmission. This data undergoes a debugging and normalization process to remove spurious peaks; in this process, the first three \"0\" bits and the \"1\" bit are removed. To eliminate the spurious peaks, the signal is subjected to a zero-crossing function, in which the mean value of the received signal is taken as the threshold normalizing the signal. Before modulation and transmission, a BR correction is also carried out, and this result is shown in Figure 6.  
This sequence of bits is modulated in QPSK format with a 5 GHz carrier signal. The modulated signal is shown in Figure 7a, whereas Figure 7b corresponds to the recovered transmitted signal affected by fast and slow fading, AWGN, propagation losses, and co-channel interference.  
\begin{table}
\begin{tabular}{c c c c} \hline \hline
**No. of Pulse** & **Sent (Seconds)** & **Recovered (Seconds)** & **Widening (Seconds)** \\ \hline
1 & 0.320 \(\times\)\(10^{-9}\) & 0.390 \(\times\)\(10^{-9}\) & 0.07 \(\times\)\(10^{-9}\) \\ \hline
2 & 0.310 \(\times\)\(10^{-9}\) &  
Figure 8a,b show the constellation diagrams corresponding to the transmitted and received signal, respectively.  
Figure 9 corresponds to the demodulated QPSK signal. Note the similitude of this graph with the results shown in Figure 5a.  
Because noise, co-channel interference, and fading impairments are factors that cause loss of information, their levels must be considered to evaluate adequate wireless reception. For this reason, statistical tests are carried out to verify the performance of the wireless stage. The distance from U1 to BS0 varies within a range from 1 to 500 m within the corresponding sector and its position determines the affectation of the co-channel interference. The noise, interference, and fading levels are modeled as a function of the standard deviation values of the random variables that determine them. This way of modeling allows different noise levels to be proposed, which is the factor with the greatest possible variation [13,14]. Considering that co-channel interference and attenuation are modeled by random variables, and assuming that the U1 user is moving within its corresponding sector, the result of the simulation is averaged in terms of SINR and BER for different noise levels. To establish the appropriate confidence interval of the wireless simulation to obtain reliable statistical data, 1000, 10,000, 30,000, 60,000, and 100,000 repetitions are performed. Therefore, the observation was made that within the interval of 60,000 to 100,000 times, the difference between the results is negligible. Thus, 60,000 repetitions is established as the confidence interval.  
Figure 10 illustrates graphically how the noise level influences the BER percentage within the procedure carried out. One can observe that from an AWGN standard deviation of \(1\times 10^{-11}\) practically all the information is recovered; this means that the system is functional with noise levels equal to or less than this value. Figure 11 shows the SINR (dB) resulting from the same AWGN standard deviation levels. At the measure that the AWGN parameter is decreased, the SINR parameter is increased. Finally, in Figure 12 we observe that the highest values of SINR cause lower values of BER.  
Figure 8: Constellation diagrams. (**a**) Transmitted QPSK signal. (**b**) Received QPSK signal.  
Figure 9: Demodulated signal.